The document proposes a color image steganography method based on pixel value differencing (PVD) in the spatial domain. It separates each color channel of a pixel into separate matrices and applies PVD separately to embed bits in a sequential order across the channels. It embeds different number of bits in different channels for increased security and quality. It overcomes the issue of pixel values exceeding the 0-255 range in previous PVD methods by selectively embedding one less bit if needed to keep values in range. Experimental results show it provides better visual quality than previous PVD methods.
Steganography Using Adaptive Pixel Value Differencing(APVD) of Gray Images Th...cscpconf
In a gray scale image the pixel value ranges from 0 to 255. But when we use pixel-value
differencing (pvd) method as image steganographic scheme, the pixel values in the stego-image
may exceed gray scale range. An adaptive steganography based on modified pixel-value
differencing through management of pixel values within the range of gray scale has been
proposed in this paper. PVD method is used and check whether the pixel value exceeds the
range on embedding. Positions where the pixel exceeds boundary has been marked and a delicate handle is used to keep the value within the range. From the experimental it is seen that the results obtained in proposed method provides with identical payload and visual fidelity of stego-image compared to the pvd method
This paper presents embedding of data in an image using pixel-value differencing technique. This scheme is used to embed large amount of data by changing the difference between two pixels so that we are able to increase the embedding capacity. There is another technique that is pixel value shifting which also increase the embedding capacity but according to this scheme capacity will increase at edge areas of image.
AN ENHANCED SEPARABLE REVERSIBLE DATA HIDING IN ENCRYPTED IMAGES USING SIDE M...Editor IJMTER
This paper proposes a scheme for Enhanced Separable Reversible Data Hiding in
Encrypted images Using Side Match. In the first step the original image is encrypted using an
encryption key. Then additional data is embedded into the image by modifying a small portion of the
encrypted image using a data hiding key. With an encrypted image containing additional data, if a
receiver has the data hiding key, he can extract the additional data. If the receiver has the encryption
key, he can decrypt the image, but cannot extract the additional data. If the receiver has both the data
hiding key and encryption key, he can extract the additional data and recover the original content by
exploiting the spatial correlation in natural images. The accuracy of data extraction is improved by
using a better scheme for measuring the smoothness of the received image, and uses the Side Match
scheme to further decrease the error rate of extracted bits.
Modified weighted embedding method for image steganographyIAEME Publication
This document proposes a modified weighted embedding method for image steganography. It begins by discussing traditional LSB substitution methods and their weaknesses. It then describes the proposed method, which embeds data by complementing LSBs in image pixels based on the decimal value of the data, rather than direct bit replacement. This is intended to provide better security while maintaining high image quality. The embedding algorithm works by converting the data to decimal, dividing the cover image into blocks, and complementing LSBs in the block pixels based on the decimal digits and an embedding table. Extraction works similarly but in reverse. Experiments on grayscale images are said to support the method.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
A new hybrid steganographic method for histogram preservation IJEEE
The document proposes a new hybrid steganographic method that embeds data in grayscale images while preserving the histogram characteristics. It uses pixel value differencing (PVD) and least significant bit (LSB) substitution. The method divides the pixel range into lower and higher levels and embeds more bits in higher levels. Each 3x3 block has a base pixel where 3 bits are embedded using LSB replacement. Remaining pixels are embedded using PVD. Experiments show it provides higher embedding capacity and image quality than existing methods while introducing fewer changes to the histogram.
A Hybrid Steganography Technique Based On LSBMR And OPAPIOSRJVSP
This paper presents a steganography technique based on two existing methods of data hiding i.e. LSBMR and OPAP. The proposed method uses the non-overlapping blocks, having three consecutive pixels. The center pixel of this block embeds k- bits of secret data using OPAP and the remaining pixels of the block embed data using LSBMR. The experimental results show that the proposed method provides better embedding capacity while maintaining the good image quality. The improved performance is shown in comparison to other data hiding methods that are investigated in this study.
This article proposes bit flipping method to conceal secret data in the original image. Here a section consists of 2 pixels and there by flipping one or two LSBs of the pixels to hide secret information in it. It exists in 2 variants. The variant-1 and variant-2 both use 7th and 8th bit to conceal the secret data. Variant-1 hides 3 bits per a pair of pixels and the variant-2 hides 4 bits per a pair of pixels. Our proposed method notably raises the capacity as well as bits per pixel that can be hidden in the image compared to existing bit flipping method. The image steganographic parameters such as, peak signal to noise ratio (PSNR), hiding capacity, and the quality index of the proposed techniques has been compared with the existing bit flipping technique.
Steganography Using Adaptive Pixel Value Differencing(APVD) of Gray Images Th...cscpconf
In a gray scale image the pixel value ranges from 0 to 255. But when we use pixel-value
differencing (pvd) method as image steganographic scheme, the pixel values in the stego-image
may exceed gray scale range. An adaptive steganography based on modified pixel-value
differencing through management of pixel values within the range of gray scale has been
proposed in this paper. PVD method is used and check whether the pixel value exceeds the
range on embedding. Positions where the pixel exceeds boundary has been marked and a delicate handle is used to keep the value within the range. From the experimental it is seen that the results obtained in proposed method provides with identical payload and visual fidelity of stego-image compared to the pvd method
This paper presents embedding of data in an image using pixel-value differencing technique. This scheme is used to embed large amount of data by changing the difference between two pixels so that we are able to increase the embedding capacity. There is another technique that is pixel value shifting which also increase the embedding capacity but according to this scheme capacity will increase at edge areas of image.
AN ENHANCED SEPARABLE REVERSIBLE DATA HIDING IN ENCRYPTED IMAGES USING SIDE M...Editor IJMTER
This paper proposes a scheme for Enhanced Separable Reversible Data Hiding in
Encrypted images Using Side Match. In the first step the original image is encrypted using an
encryption key. Then additional data is embedded into the image by modifying a small portion of the
encrypted image using a data hiding key. With an encrypted image containing additional data, if a
receiver has the data hiding key, he can extract the additional data. If the receiver has the encryption
key, he can decrypt the image, but cannot extract the additional data. If the receiver has both the data
hiding key and encryption key, he can extract the additional data and recover the original content by
exploiting the spatial correlation in natural images. The accuracy of data extraction is improved by
using a better scheme for measuring the smoothness of the received image, and uses the Side Match
scheme to further decrease the error rate of extracted bits.
Modified weighted embedding method for image steganographyIAEME Publication
This document proposes a modified weighted embedding method for image steganography. It begins by discussing traditional LSB substitution methods and their weaknesses. It then describes the proposed method, which embeds data by complementing LSBs in image pixels based on the decimal value of the data, rather than direct bit replacement. This is intended to provide better security while maintaining high image quality. The embedding algorithm works by converting the data to decimal, dividing the cover image into blocks, and complementing LSBs in the block pixels based on the decimal digits and an embedding table. Extraction works similarly but in reverse. Experiments on grayscale images are said to support the method.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
A new hybrid steganographic method for histogram preservation IJEEE
The document proposes a new hybrid steganographic method that embeds data in grayscale images while preserving the histogram characteristics. It uses pixel value differencing (PVD) and least significant bit (LSB) substitution. The method divides the pixel range into lower and higher levels and embeds more bits in higher levels. Each 3x3 block has a base pixel where 3 bits are embedded using LSB replacement. Remaining pixels are embedded using PVD. Experiments show it provides higher embedding capacity and image quality than existing methods while introducing fewer changes to the histogram.
A Hybrid Steganography Technique Based On LSBMR And OPAPIOSRJVSP
This paper presents a steganography technique based on two existing methods of data hiding i.e. LSBMR and OPAP. The proposed method uses the non-overlapping blocks, having three consecutive pixels. The center pixel of this block embeds k- bits of secret data using OPAP and the remaining pixels of the block embed data using LSBMR. The experimental results show that the proposed method provides better embedding capacity while maintaining the good image quality. The improved performance is shown in comparison to other data hiding methods that are investigated in this study.
This article proposes bit flipping method to conceal secret data in the original image. Here a section consists of 2 pixels and there by flipping one or two LSBs of the pixels to hide secret information in it. It exists in 2 variants. The variant-1 and variant-2 both use 7th and 8th bit to conceal the secret data. Variant-1 hides 3 bits per a pair of pixels and the variant-2 hides 4 bits per a pair of pixels. Our proposed method notably raises the capacity as well as bits per pixel that can be hidden in the image compared to existing bit flipping method. The image steganographic parameters such as, peak signal to noise ratio (PSNR), hiding capacity, and the quality index of the proposed techniques has been compared with the existing bit flipping technique.
Ieee a secure algorithm for image based information hiding with one-dimension...Akash Rawat
ieee a secure algorithm for image based information hiding with one-dimensional chaotic systems.It used 1 dimensional chaotic system.ieee paper related for image encryption
This new algorithm mixes two or more images of different types and sizes by employing a shuffling
procedure combined with S-box substitution to perform lossless image encryption. This combines stream
cipher with block cipher, on the byte level, in mixing the images. When this algorithm was implemented,
empirical analysis using test images of different types and sizes showed that it is effective and resistant to
attacks.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Image steganography techniques can be classified into two major categories such as spatial domain techniques and frequency domain techniques.
In spatial domain techniques the secret message is hidden inside the image by applying some manipulation over the different pixels of the image.
In frequency domain techniques the image is transformed to another form by applying a transformation like discrete wavelet transform and then the message is hidden by applying any of the usual embedding techniques.
This document summarizes a research paper that proposes a novel reversible data hiding scheme using AES encryption. The scheme consists of three phases: 1) AES encryption of the original image, 2) data embedding by modifying parts of the encrypted image, 3) data extraction and image recovery by decrypting the encrypted image and extracting the hidden data. The scheme aims to securely hide data in images while allowing perfect recovery of the original image. Experimental results show the decrypted image has a high PSNR value of 55.11dB and the hidden data can be successfully extracted.
New Approach of Preprocessing For Numeral RecognitionIJERA Editor
The present paper proposes a new approach of preprocessing for handwritten, printed and isolated numeral
characters. The new approach reduces the size of the input image of each numeral by discarding the redundant
information. This method reduces also the number of features of the attribute vector provided by the extraction
features method. Numeral recognition is carried out in this work through k nearest neighbors and multilayer
perceptron techniques. The simulations have obtained a good rate of recognition in fewer running time.
A new block cipher for image encryption based on multi chaotic systemsTELKOMNIKA JOURNAL
In this paper, a new algorithm for image encryption is proposed based on three chaotic systems which are Chen system,logistic map and two-dimensional (2D) Arnold cat map. First, a permutation scheme is applied to the image, and then shuffled image is partitioned into blocks of pixels. For each block, Chen system is employed for confusion and then logistic map is employed for generating subsititution-box (S-box) to substitute image blocks. The S-box is dynamic, where it is shuffled for each image block using permutation operation. Then, 2D Arnold cat map is used for providing diffusion, after that XORing the result using Chen system to obtain the encrypted image.The high security of proposed algorithm is experimented using histograms, unified average changing intensity (UACI), number of pixels change rate (NPCR), entropy, correlation and keyspace analyses.
Concealogram digital image in image using lsb insertion methodIAEME Publication
This document summarizes a research paper that proposes a new algorithm for concealing a digital image within a cover image. The algorithm uses spatial domain techniques like least significant bit insertion to hide image data in the cover image. It describes two methods - a 4-bit method that embeds 4 most significant bits of the secret image into the 4 least significant bits of the cover image pixels. A 6-bit method is also described that embeds 6 bits of the secret image across two pixels of the cover image. The document concludes by mentioning that the algorithm was tested using peak signal-to-noise ratio to measure stego image quality.
Performance Improvement of Vector Quantization with Bit-parallelism HardwareCSCJournals
Vector quantization is an elementary technique for image compression; however, searching for the nearest codeword in a codebook is time-consuming. In this work, we propose a hardware-based scheme by adopting bit-parallelism to prune unnecessary codewords. The new scheme uses a “Bit-mapped Look-up Table” to represent the positional information of the codewords. The lookup procedure can simply refer to the bitmaps to find the candidate codewords. Our simulation results further confirm the effectiveness of the proposed scheme.
Efficient & Secure Data Hiding Using Secret Reference MatrixIJNSA Journal
Steganography is the science of secret message delivery using cover media. The cover carriers can be image, video, sound or text data. A digital image is a flexible medium used to carry a secret message because the slight modification of a cover image is hard to distinguish by human eyes. The proposed method is inspired from Chang method of Secret Reference Matrix. The data is hidden in 8 bit gray scale image using 256 X 256 matrix which is constructed by using 4 x 4 table with unrepeated digits from 0~15. The proposed method has high hiding capacity, better stego-image quality, requires little calculation and is easy to implement.
Quality Measurements of Lossy Image Steganography Based on H-AMBTC Technique ...AM Publications,India
This document presents a new technique called H-AMBTC (Hadamard-Absolute Moment Block Truncation Coding) for lossy image steganography. H-AMBTC combines Hadamard transformation with AMBTC (Absolute Moment Block Truncation Coding) to compress cover images and conceal secret data within them. The document describes the H-AMBTC encoding and decoding algorithms and compares its performance using different block sizes (2x2, 4x4, 8x8, 16x16) based on PSNR values. Results show that 16x16 blocks provided the best PSNR for test images, indicating higher quality of the stego-images produced by the H-AMBTC technique compared to smaller block sizes
The document discusses DCT (Discrete Cosine Transform) based steganography. It introduces steganography and some examples of its historical uses. It then summarizes the basics of DCT, why it is useful for steganography, an example steganography algorithm that embeds messages in the DCT coefficients of images, and possibilities for future improvements like using both steganography and cryptography for increased security. The presentation was created by a group of students for their steganography project.
Fuzzy Encoding For Image Classification Using Gustafson-Kessel AglorithmAshish Gupta
This paper presents a novel adaptation of fuzzy clustering and
feature encoding for image classification. Visual word ambiguity
has recently been successfully modeled by kernel codebooks
to provide improvement in classification performance
over the standard ‘Bag-of-Features’(BoF) approach, which
uses hard partitioning and crisp logic for assignment of features
to visual words. Motivated by this progress we utilize
fuzzy logic to model the ambiguity and combine it with clustering
to discover fuzzy visual words. The feature descriptors
of an image are encoded using the learned fuzzy membership
function associated with each word. The codebook built
using this fuzzy encoding technique is demonstrated to provide
superior performance over BoF. We use the Gustafson-
Kessel algorithm which is an improvement over Fuzzy CMeans
clustering and can adapt to local distributions. We
evaluate our approach on several popular datasets and demonstrate
that it consistently provides superior performance to the
BoF approach.
Reversible Data Hiding in the Spatial and Frequency DomainsCSCJournals
Combinational lossless data hiding in the spatial and frequency domains is proposed. In the spatial domain, a secret message is embedded in a host medium using the min-max algorithm to generate a stego-image. Subsequently, the stego-image is decomposed into the frequency domain via the integer wavelet transform (IWT). Then, a watermark is hidden in the low-high (LH) and high-low (HL) subbands of the IWT domain using the coefficient-bias approach. Simulations show that the perceptual quality of the image generated by the proposed method and the method¡¦s hiding capability are good. Moreover, the mixed images produced by the proposed method are robust against attacks such as JPEG2000, JPEG, brightness adjustment, and inversion.
This document discusses parallelizing object detection in videos for many-core systems. It presents an object detection algorithm that includes frame differencing, background differencing, post-processing, and background updating. The algorithm is parallelized by vertically partitioning video frames across cores, with some pixel overlap between partitions to reduce communication overhead. The parallel implementation achieves a speedup of 37.2x on a 64-core Tilera system processing 18 full-HD frames per second. A performance prediction equation is also developed and shown to accurately model the real performance results.
This document discusses using fuzzy clustering to group real estate properties. It presents a case study clustering 46 real estate listings into 3 groups based on price, area, and region attributes. The fuzzy c-means clustering algorithm in MATLAB is used to assign membership levels and cluster centroids. The results identify 3 clusters - one for mid-priced properties in good regions and average areas, one for high-priced properties in excellent regions and large areas, and one for low-priced properties in poor regions and small areas. Graphs and tables show the clustered properties and centroids.
Chaos Image Encryption using Pixel shuffling cscpconf
This document proposes a chaos-based image encryption algorithm using pixel shuffling. It uses elements from a chaotic map like the Henon map or Lorentz map to shuffle the pixel positions of an image. The chaotic elements are divided into blocks corresponding to the RGB channels. Pixel positions are reordered according to the sorted indices of each block. Encryption scrambles the pixel positions, while decryption restores the original positions using the same chaotic map. Experimental results on brain and Lena images show the encrypted images have very low correlation with the originals. Slight key changes also result in completely different decryptions, demonstrating key sensitivity of the algorithm.
This paper describes a novel system for vectorizing 2D raster cartoon. The output videos are the resolution independent, smaller in file size. As a first step, input video is segment to scene thereafter all processes are done for each scene separately. Every scene contains foreground and background objects so in each and every scene foreground background classification is performed. Background details can occlude by foreground objects but when foreground objects move its previous position such occluded details exposed in one of the next frame so using that frame can fill the occluded area and can generate static background. Classified foreground objects are identified and the motion of the foreground objects tracked for this simple user assistance is required from those motion details of foreground object’s animation generated. Static background and foreground objects segmented using K-means clustering and each and every cluster’s vectorized using potrace. Using vectored background and foreground object animation path vector video regenerated.
Histogram-based multilayer reversible data hiding method for securing secret ...journalBEEI
In this modern age, data can be easily transferred within networks. This condition has brought the data vulnerable; so they need protection at all times. To minimize this threat, data hiding appears as one of the potential methods to secure data. This protection is done by embedding the secret into various types of data, such as an image. In this case, histogram shifting has been proposed; however, the amount of secret and the respective stego image are still challenging. In this research, we offer a method to improve its performance by performing some steps, for example removing the shifting process and employing multilayer embedding. Here, the embedding is done directly to the peak of the histogram which has been generated by the cover. The experimental results show that this proposed method has a better quality of stego image than existing ones. So, it can be one of possible solutions to protect sensitive data.
This document summarizes and implements an ordinary differential equation (ODE) neural network using the Diffeqflux.jl library. It begins with an introduction to deep learning and neural networks. It then provides the mathematics behind modeling a simple multi-layer perceptron neural network as a system of ODEs. This includes derivations of the forward and backward propagation algorithms. Finally, it describes implementing a simple example ODE neural network using Diffeqflux.jl to demonstrate the approach.
A Novel Method for Image Watermarking Using Luminance Based Block Selection a...IJERA Editor
A robust watermark scheme for copyright protection is proposed in the present paper. The present method selects the pixel locations to insert the watermark by checking luminance [1] values of blocks. The watermark is embedded in the selected pixel blocks by using local area pixel value difference method. The proposed approach overcomes the weak robustness problem of embedding the watermark in the spatial domain and also in pixel value difference method. Further the watermark extraction does not require the original image as in the case of many digital watermarking methods. The experimental results indicate the high image quality and robustness against various attacks when compared to several approaches.
The document proposes a new hybrid steganographic method that embeds data in grayscale images while preserving the histogram characteristics. It uses pixel value differencing (PVD) and least significant bit (LSB) substitution. The method divides the pixel range into lower and higher levels and embeds more bits in higher levels. Each 3x3 block has a base pixel where 3 bits are embedded using LSB replacement. Remaining pixels are embedded using PVD. Experiments show it provides higher embedding capacity and image quality than existing methods, while introducing fewer changes to the histogram.
Ieee a secure algorithm for image based information hiding with one-dimension...Akash Rawat
ieee a secure algorithm for image based information hiding with one-dimensional chaotic systems.It used 1 dimensional chaotic system.ieee paper related for image encryption
This new algorithm mixes two or more images of different types and sizes by employing a shuffling
procedure combined with S-box substitution to perform lossless image encryption. This combines stream
cipher with block cipher, on the byte level, in mixing the images. When this algorithm was implemented,
empirical analysis using test images of different types and sizes showed that it is effective and resistant to
attacks.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Image steganography techniques can be classified into two major categories such as spatial domain techniques and frequency domain techniques.
In spatial domain techniques the secret message is hidden inside the image by applying some manipulation over the different pixels of the image.
In frequency domain techniques the image is transformed to another form by applying a transformation like discrete wavelet transform and then the message is hidden by applying any of the usual embedding techniques.
This document summarizes a research paper that proposes a novel reversible data hiding scheme using AES encryption. The scheme consists of three phases: 1) AES encryption of the original image, 2) data embedding by modifying parts of the encrypted image, 3) data extraction and image recovery by decrypting the encrypted image and extracting the hidden data. The scheme aims to securely hide data in images while allowing perfect recovery of the original image. Experimental results show the decrypted image has a high PSNR value of 55.11dB and the hidden data can be successfully extracted.
New Approach of Preprocessing For Numeral RecognitionIJERA Editor
The present paper proposes a new approach of preprocessing for handwritten, printed and isolated numeral
characters. The new approach reduces the size of the input image of each numeral by discarding the redundant
information. This method reduces also the number of features of the attribute vector provided by the extraction
features method. Numeral recognition is carried out in this work through k nearest neighbors and multilayer
perceptron techniques. The simulations have obtained a good rate of recognition in fewer running time.
A new block cipher for image encryption based on multi chaotic systemsTELKOMNIKA JOURNAL
In this paper, a new algorithm for image encryption is proposed based on three chaotic systems which are Chen system,logistic map and two-dimensional (2D) Arnold cat map. First, a permutation scheme is applied to the image, and then shuffled image is partitioned into blocks of pixels. For each block, Chen system is employed for confusion and then logistic map is employed for generating subsititution-box (S-box) to substitute image blocks. The S-box is dynamic, where it is shuffled for each image block using permutation operation. Then, 2D Arnold cat map is used for providing diffusion, after that XORing the result using Chen system to obtain the encrypted image.The high security of proposed algorithm is experimented using histograms, unified average changing intensity (UACI), number of pixels change rate (NPCR), entropy, correlation and keyspace analyses.
Concealogram digital image in image using lsb insertion methodIAEME Publication
This document summarizes a research paper that proposes a new algorithm for concealing a digital image within a cover image. The algorithm uses spatial domain techniques like least significant bit insertion to hide image data in the cover image. It describes two methods - a 4-bit method that embeds 4 most significant bits of the secret image into the 4 least significant bits of the cover image pixels. A 6-bit method is also described that embeds 6 bits of the secret image across two pixels of the cover image. The document concludes by mentioning that the algorithm was tested using peak signal-to-noise ratio to measure stego image quality.
Performance Improvement of Vector Quantization with Bit-parallelism HardwareCSCJournals
Vector quantization is an elementary technique for image compression; however, searching for the nearest codeword in a codebook is time-consuming. In this work, we propose a hardware-based scheme by adopting bit-parallelism to prune unnecessary codewords. The new scheme uses a “Bit-mapped Look-up Table” to represent the positional information of the codewords. The lookup procedure can simply refer to the bitmaps to find the candidate codewords. Our simulation results further confirm the effectiveness of the proposed scheme.
Efficient & Secure Data Hiding Using Secret Reference MatrixIJNSA Journal
Steganography is the science of secret message delivery using cover media. The cover carriers can be image, video, sound or text data. A digital image is a flexible medium used to carry a secret message because the slight modification of a cover image is hard to distinguish by human eyes. The proposed method is inspired from Chang method of Secret Reference Matrix. The data is hidden in 8 bit gray scale image using 256 X 256 matrix which is constructed by using 4 x 4 table with unrepeated digits from 0~15. The proposed method has high hiding capacity, better stego-image quality, requires little calculation and is easy to implement.
Quality Measurements of Lossy Image Steganography Based on H-AMBTC Technique ...AM Publications,India
This document presents a new technique called H-AMBTC (Hadamard-Absolute Moment Block Truncation Coding) for lossy image steganography. H-AMBTC combines Hadamard transformation with AMBTC (Absolute Moment Block Truncation Coding) to compress cover images and conceal secret data within them. The document describes the H-AMBTC encoding and decoding algorithms and compares its performance using different block sizes (2x2, 4x4, 8x8, 16x16) based on PSNR values. Results show that 16x16 blocks provided the best PSNR for test images, indicating higher quality of the stego-images produced by the H-AMBTC technique compared to smaller block sizes
The document discusses DCT (Discrete Cosine Transform) based steganography. It introduces steganography and some examples of its historical uses. It then summarizes the basics of DCT, why it is useful for steganography, an example steganography algorithm that embeds messages in the DCT coefficients of images, and possibilities for future improvements like using both steganography and cryptography for increased security. The presentation was created by a group of students for their steganography project.
Fuzzy Encoding For Image Classification Using Gustafson-Kessel AglorithmAshish Gupta
This paper presents a novel adaptation of fuzzy clustering and
feature encoding for image classification. Visual word ambiguity
has recently been successfully modeled by kernel codebooks
to provide improvement in classification performance
over the standard ‘Bag-of-Features’(BoF) approach, which
uses hard partitioning and crisp logic for assignment of features
to visual words. Motivated by this progress we utilize
fuzzy logic to model the ambiguity and combine it with clustering
to discover fuzzy visual words. The feature descriptors
of an image are encoded using the learned fuzzy membership
function associated with each word. The codebook built
using this fuzzy encoding technique is demonstrated to provide
superior performance over BoF. We use the Gustafson-
Kessel algorithm which is an improvement over Fuzzy CMeans
clustering and can adapt to local distributions. We
evaluate our approach on several popular datasets and demonstrate
that it consistently provides superior performance to the
BoF approach.
Reversible Data Hiding in the Spatial and Frequency DomainsCSCJournals
Combinational lossless data hiding in the spatial and frequency domains is proposed. In the spatial domain, a secret message is embedded in a host medium using the min-max algorithm to generate a stego-image. Subsequently, the stego-image is decomposed into the frequency domain via the integer wavelet transform (IWT). Then, a watermark is hidden in the low-high (LH) and high-low (HL) subbands of the IWT domain using the coefficient-bias approach. Simulations show that the perceptual quality of the image generated by the proposed method and the method¡¦s hiding capability are good. Moreover, the mixed images produced by the proposed method are robust against attacks such as JPEG2000, JPEG, brightness adjustment, and inversion.
This document discusses parallelizing object detection in videos for many-core systems. It presents an object detection algorithm that includes frame differencing, background differencing, post-processing, and background updating. The algorithm is parallelized by vertically partitioning video frames across cores, with some pixel overlap between partitions to reduce communication overhead. The parallel implementation achieves a speedup of 37.2x on a 64-core Tilera system processing 18 full-HD frames per second. A performance prediction equation is also developed and shown to accurately model the real performance results.
This document discusses using fuzzy clustering to group real estate properties. It presents a case study clustering 46 real estate listings into 3 groups based on price, area, and region attributes. The fuzzy c-means clustering algorithm in MATLAB is used to assign membership levels and cluster centroids. The results identify 3 clusters - one for mid-priced properties in good regions and average areas, one for high-priced properties in excellent regions and large areas, and one for low-priced properties in poor regions and small areas. Graphs and tables show the clustered properties and centroids.
Chaos Image Encryption using Pixel shuffling cscpconf
This document proposes a chaos-based image encryption algorithm using pixel shuffling. It uses elements from a chaotic map like the Henon map or Lorentz map to shuffle the pixel positions of an image. The chaotic elements are divided into blocks corresponding to the RGB channels. Pixel positions are reordered according to the sorted indices of each block. Encryption scrambles the pixel positions, while decryption restores the original positions using the same chaotic map. Experimental results on brain and Lena images show the encrypted images have very low correlation with the originals. Slight key changes also result in completely different decryptions, demonstrating key sensitivity of the algorithm.
This paper describes a novel system for vectorizing 2D raster cartoon. The output videos are the resolution independent, smaller in file size. As a first step, input video is segment to scene thereafter all processes are done for each scene separately. Every scene contains foreground and background objects so in each and every scene foreground background classification is performed. Background details can occlude by foreground objects but when foreground objects move its previous position such occluded details exposed in one of the next frame so using that frame can fill the occluded area and can generate static background. Classified foreground objects are identified and the motion of the foreground objects tracked for this simple user assistance is required from those motion details of foreground object’s animation generated. Static background and foreground objects segmented using K-means clustering and each and every cluster’s vectorized using potrace. Using vectored background and foreground object animation path vector video regenerated.
Histogram-based multilayer reversible data hiding method for securing secret ...journalBEEI
In this modern age, data can be easily transferred within networks. This condition has brought the data vulnerable; so they need protection at all times. To minimize this threat, data hiding appears as one of the potential methods to secure data. This protection is done by embedding the secret into various types of data, such as an image. In this case, histogram shifting has been proposed; however, the amount of secret and the respective stego image are still challenging. In this research, we offer a method to improve its performance by performing some steps, for example removing the shifting process and employing multilayer embedding. Here, the embedding is done directly to the peak of the histogram which has been generated by the cover. The experimental results show that this proposed method has a better quality of stego image than existing ones. So, it can be one of possible solutions to protect sensitive data.
This document summarizes and implements an ordinary differential equation (ODE) neural network using the Diffeqflux.jl library. It begins with an introduction to deep learning and neural networks. It then provides the mathematics behind modeling a simple multi-layer perceptron neural network as a system of ODEs. This includes derivations of the forward and backward propagation algorithms. Finally, it describes implementing a simple example ODE neural network using Diffeqflux.jl to demonstrate the approach.
A Novel Method for Image Watermarking Using Luminance Based Block Selection a...IJERA Editor
A robust watermark scheme for copyright protection is proposed in the present paper. The present method selects the pixel locations to insert the watermark by checking luminance [1] values of blocks. The watermark is embedded in the selected pixel blocks by using local area pixel value difference method. The proposed approach overcomes the weak robustness problem of embedding the watermark in the spatial domain and also in pixel value difference method. Further the watermark extraction does not require the original image as in the case of many digital watermarking methods. The experimental results indicate the high image quality and robustness against various attacks when compared to several approaches.
The document proposes a new hybrid steganographic method that embeds data in grayscale images while preserving the histogram characteristics. It uses pixel value differencing (PVD) and least significant bit (LSB) substitution. The method divides the pixel range into lower and higher levels and embeds more bits in higher levels. Each 3x3 block has a base pixel where 3 bits are embedded using LSB replacement. Remaining pixels are embedded using PVD. Experiments show it provides higher embedding capacity and image quality than existing methods, while introducing fewer changes to the histogram.
Efficient Technique for Image Stenography Based on coordinates of pixelsIOSR Journals
This document proposes a novel image steganography technique based on pixel pair matching. The technique uses "diamond encoding" to embed secret data by adjusting pixel values in image blocks. It can conceal a (2k^2 + 2k + 1)-ary digit into each pixel pair by modifying at most one pixel value. The embedding and extraction processes are described. Experimental results on test images like Lena show the technique can hide more secret data while maintaining good stego-image quality as measured by PSNR, outperforming simple LSB substitution methods.
A Robust Image Watermarking Technique using Luminance Based Area Selection an...IRJET Journal
This summarizes a document describing a robust image watermarking technique using luminance-based area selection and block pixel value differencing (PVD). It embeds watermarks in selected blocks of an image based on the difference between pixel values. Blocks are selected based on their log-average luminance being close to the overall image luminance. Within blocks, pixel pairs with the highest differences are used to embed bits by modifying the difference values. The technique aims to improve embedding capacity and imperceptibility while maintaining image quality as measured by PSNR and MSE metrics. It shows robustness against various attacks.
An Improved Adaptive Steganographic Method Based on Least Significant Bit Sub...IOSRJVSP
This paper presents a novel technique for improved data embedding in cover images based on least significant bit and pixel-value differencing. The proposed method is based on the properties of human visual system i.e. eyes can tolerate larger changes in edge areas as compared to smooth areas. Therefore, the method utilizes the HVS concept and hides large amount of secret data in edge areas while less amount of data in smooth areas. The results of the proposed method are verified using extensive simulations.
This document summarizes different pixel value differencing (PVD) techniques for image steganography. It discusses the original PVD method proposed in 2003 and several improvements and variations that have been proposed since, including modified PVD, adaptive PVD, modulus PVD, multi-directional PVD, multi-pixel differencing PVD using 3, 4, 5, 9 pixels, and techniques that combine PVD with LSB substitution or embedding in frequency domains. The document concludes that better techniques are needed for color images and edge-based images.
This document summarizes research on using the Pixel Value Differencing (PVD) steganography algorithm to hide text messages in color medical images for telemedicine applications. The PVD algorithm works by comparing the pixel values of neighboring pixels and inserting message bits based on the difference range, allowing more bits to be hidden in high contrast areas. The study tested hiding 10KB, 20KB, and 30KB texts in high and low object density medical images. For high density images, the PVD algorithm maintained a PSNR above 57.98dB for 10KB text with an MSE of 0.05 or lower. For telemedicine, PVD steganography can securely transmit confidential medical texts within color images while maintaining good image quality
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Implementation of LSB-Based Image Steganography Method for effectiveness of D...ijsrd.com
Increased use of electronic communication has given birth to new ways of transmitting information securely. Steganography is a science of hiding information by embedding it in some other data called host message. Images are most known objects for steganography. The host message before steganography and stego message after steganography have the same characteristics. The given work is to be done by evaluating it on MATALAB. While evaluation one can calculate SNR, PSNR and BER for individual information Bit for conceal bit and analysis effect on results.
A Survey of different Data Hiding Techniques in Digital Imagesijsrd.com
Steganography is the art and science of invisible communication, which hides the existence of the communicated message into media such as text, audio, image and video without any suspicion. Steganography is different from cryptography and watermarking in its objectives which includes undetectability, robustness (resistance to various image processing methods and compression) and capacity of the hidden data. Image Steganography uses digital image as its cover media. This paper analyzes and discusses various techniques available today for image steganography along with their strengths and weaknesses.
This document proposes an efficient data steganography method called Adaptive Pixel Pair Matching (APPM) with high security. APPM hides data by substituting pixel pairs in a cover image based on a secret key. It defines an extraction function and compact neighborhood set for pixel pairs to minimize embedding distortion. APPM converts the secret message into digits of a B-ary numerical system for hiding. It calculates the optimal value of B and neighborhood set based on the image and message size. APPM generates a random embedding sequence using a key for substitution. It also provides an external password for additional security of the hidden message. The document claims this method provides better image quality and higher payload than previous pixel pair matching methods with increased security.
Hybrid Technique for Copy-Move Forgery Detection Using L*A*B* Color Space IJEEE
Copy-move forgery is applied on an image to hide a region or an object. Most of the detection techniques either use transform domain or spatial domain information to detect the forgery. This paper presents a hybrid method to detect the forgery making use of both the domains i.e. transform domain in whichSVD is used to extract the useful information from image and spatial domain in which L*a*b* color space is used. Here block based approach and lexicographical sorting is used to group matching feature vectors. Obtained experimental results demonstrate that proposed method efficiently detects copy-move forgery even when post-processing operations like blurring, noise contamination, and severe lossy compression are applied.
DCT based Steganographic Evaluation parameter analysis in Frequency domain by...IOSR Journals
This document analyzes DCT-based steganography using a modified JPEG luminance quantization table to improve evaluation parameters like PSNR, mean square error, and capacity. The authors propose modifying the default 8x8 quantization table by adjusting frequency values in 4 bands to increase image quality for the embedded stego image. Experimental results on test images show that using the modified table improves PSNR, decreases mean square error, and increases maximum embedding capacity compared to the default table. Therefore, the proposed method allows more secret data to be hidden with less distortion and improved image quality.
This document analyzes DCT-based steganography using a modified JPEG luminance quantization table to improve embedding capacity and image quality. The authors propose modifying the default 8x8 quantization table by changing frequency values to increase the peak signal-to-noise ratio and capacity while decreasing the mean square error of embedded images. Experimental results on test images show increased capacity, PSNR and reduced error when using the modified versus default table, indicating improved stego image quality. The proposed method aims to securely embed more data with less distortion than traditional DCT-based steganography.
A secure image steganography based on JND model IJECEIAES
This document presents a new secure image steganography method based on the Just Noticeable Difference (JND) model. The method uses a modified matrix encoding technique to embed secret bits into cover images. It selects pixels for embedding by calculating the JND value and average gradient of each pixel, and choosing the pixel associated with the smallest estimated embedding distortion. Experimental results on a database of 10,000 images show that stego images produced with the proposed approach achieve higher perceptual quality and security than previous approaches.
A Secure Color Image Steganography in Transform Domain ijcisjournal
Steganography is the art and science of covert communication. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted image is also similar to the secret image. This is proved by the high PSNR (Peak Signal to Noise Ratio), value for both stego and extracted secret image. The results are compared with the results of similar techniques and it is found that the proposed technique is simple and gives better PSNR values than others.
This document presents a technique for steganography using the least significant bit (LSB) and an encryption method. It discusses how the LSB technique works by replacing the LSB of pixels in a cover image with bits from a secret image. It then proposes encrypting the LSB plane of the encoded image by altering its columns at regular intervals before generating the stego image. This increases security by making it harder to extract the secret image through steganalysis while maintaining image quality. MATLAB code demonstrates embedding a secret image in a cover image using LSB, encrypting the LSB plane, generating the stego image, and successfully extracting the secret image.
IRJET- An Improved 2LSB Steganography Technique for Data TransmissionIRJET Journal
This document proposes an improved 2LSB steganography technique for hiding data in digital images. The technique embeds message bits randomly into the least significant bit planes of pixels in an RGB image. It uses the two least significant bits of the red channel to indicate whether even or odd parity bits of the message will be embedded in the green and blue channels. The random embedding of bits and parity checks makes the hidden message difficult to detect. Experimental results show the technique can hide message bits in 65-74% of pixels while maintaining good image quality with PSNR values over 30dB. The technique aims to provide higher data hiding capacity and security compared to standard 2LSB steganography.
Protecting Data by Improving Quality of Stego Image based on Enhanced Reduced...IJECEIAES
In this era of internet development, security of information sharing is the main problem faced by human being. Data hiding technique is one of the solutions. However, hiding credential information within a multimedia file such as image reduces its visual quality. Therefore, unauthorized users may suspect the existance of secret data within that image. In the past years, various data hiding algorithms have been developed by researchers to overcome the problem of high distortion of image after data embedding process. Achieving a high quality stego image, however, is still a challenging problem. In this paper, we proposed a new data hiding algorithm based on different expansion. It aims to enhance the quality of stego image for a given payload size. The new algorithm is evaluated on various medical images. Thereafter, the experimental results show that the visual quality is improved; and increasing the embedding capacity leads to more noises. Therefore, a better choice of base point and a reduced difference expansion affect the quality of stego image.
High Security Cryptographic Technique Using Steganography and Chaotic Image E...IOSR Journals
This document summarizes a proposed cryptographic technique that combines steganography and chaotic image encryption to provide high security. Steganography is used to hide a message within a cover image by embedding it in the least significant bits of pixel values without affecting image quality. The resulting stego-image is then encrypted using triple-key chaotic image encryption based on the logistic map, making the encrypted data highly sensitive to changes in the initial encryption keys. The technique provides four layers of security to securely transmit hidden messages within digital images.
Similar to Colour Image Steganography Based on Pixel Value Differencing in Spatial Domain (20)
Call for Papers - 5th International Conference on Cloud, Big Data and IoT (CB...ijistjournal
5th International Conference on Cloud, Big Data and IoT (CBIoT 2024) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Cloud, Big Data and IoT.
PERFORMANCE ANALYSIS OF PARALLEL IMPLEMENTATION OF ADVANCED ENCRYPTION STANDA...ijistjournal
Cryptography is the study of mathematical techniques related to aspects of information security such as confidentiality, data integrity, entity authentication, and data origin authentication. Most cryptographic algorithms function more efficiently when implemented in hardware than in software running on single processor. However, systems that use hardware implementations have significant drawbacks: they are unable to respond to flaws discovered in the implemented algorithm or to changes in standards. As an alternative, it is possible to implement cryptographic algorithms in software running on multiple processors. However, most of the cryptographic algorithms like DES (Data Encryption Standard) or 3DES have some drawbacks when implemented in software: DES is no longer secure as computers get more powerful while 3DES is relatively sluggish in software. AES (Advanced Encryption Standard), which is rapidly being adopted worldwide, provides a better combination of performance and enhanced network security than DES or 3DES by being computationally more efficient than these earlier standards. Furthermore, by supporting large key sizes of 128, 192, and 256 bits, AES offers higher security against brute-force attacks.
In this paper, AES has been implemented with single processor. Then the result has been compared with parallel implementations of AES with 2 varying different parameters such as key size, number of rounds and extended key size, and show how parallel implementation of the AES offers better performance yet flexible enough for cryptographic algorithms.
Submit Your Research Articles - International Journal of Information Sciences...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
INFORMATION THEORY BASED ANALYSIS FOR UNDERSTANDING THE REGULATION OF HLA GEN...ijistjournal
Considering information entropy (IE), HLA surface expression (SE) regulation phenomenon is considered as information propagation channel with an amount of distortion. HLA gene SE is considered as sink regulated by the inducible transcription factors (TFs) (source). Previous work with a certain number of bin size, IEs for source and receiver is computed and computation of mutual information characterizes the dependencies of HLA gene SE on some certain TFs in different cells types of hematopoietic system under the condition of leukemia. Though in recent time information theory is utilized for different biological knowledge generation and different rules are available in those specific domains of biomedical areas; however, no such attempt is made regarding gene expression regulation, hence no such rule is available. In this work, IE calculation with varying bin size considering the number of bins is approximately half of the sample size of an attribute also confirms the previous inferences.
Call for Research Articles - 5th International Conference on Artificial Intel...ijistjournal
5th International Conference on Artificial Intelligence and Machine Learning (CAIML 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science, Engineering and Applications.
Online Paper Submission - International Journal of Information Sciences and T...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
SYSTEM IDENTIFICATION AND MODELING FOR INTERACTING AND NON-INTERACTING TANK S...ijistjournal
System identification from the experimental data plays a vital role for model based controller design. Derivation of process model from first principles is often difficult due to its complexity. The first stage in the development of any control and monitoring system is the identification and modeling of the system. Each model is developed within the context of a specific control problem. Thus, the need for a general system identification framework is warranted. The proposed framework should be able to adapt and emphasize different properties based on the control objective and the nature of the behavior of the system. Therefore, system identification has been a valuable tool in identifying the model of the system based on the input and output data for the design of the controller. The present work is concerned with the identification of transfer function models using statistical model identification, process reaction curve method, ARX model, genetic algorithm and modeling using neural network and fuzzy logic for interacting and non interacting tank process. The identification technique and modeling used is prone to parameter change & disturbance. The proposed methods are used for identifying the mathematical model and intelligent model of interacting and non interacting process from the real time experimental data.
Call for Research Articles - 4th International Conference on NLP & Data Minin...ijistjournal
4th International Conference on NLP & Data Mining (NLDM 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Data Mining.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.
Research Article Submission - International Journal of Information Sciences a...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
Call for Papers - International Journal of Information Sciences and Technique...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
Implementation of Radon Transformation for Electrical Impedance Tomography (EIT)ijistjournal
Radon Transformation is generally used to construct optical image (like CT image) from the projection data in biomedical imaging. In this paper, the concept of Radon Transformation is implemented to reconstruct Electrical Impedance Topographic Image (conductivity or resistivity distribution) of a circular subject. A parallel resistance model of a subject is proposed for Electrical Impedance Topography(EIT) or Magnetic Induction Tomography(MIT). A circular subject with embedded circular objects is segmented into equal width slices from different angles. For each angle, Conductance and Conductivity of each slice is calculated and stored in an array. A back projection method is used to generate a two-dimensional image from one-dimensional projections. As a back projection method, Inverse Radon Transformation is applied on the calculated conductance and conductivity to reconstruct two dimensional images. These images are compared to the target image. In the time of image reconstruction, different filters are used and these images are compared with each other and target image.
Online Paper Submission - 6th International Conference on Machine Learning & ...ijistjournal
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.
Submit Your Research Articles - International Journal of Information Sciences...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
BER Performance of MPSK and MQAM in 2x2 Almouti MIMO Systemsijistjournal
Almouti published the error performance of the 2x2 space-time transmit diversity scheme using BPSK. One of the key techniques employed for correcting such errors is the Quadrature amplitude modulation (QAM) because of its efficiency in power and bandwidth.. In this paper we explore the error performance of the 2x2 MIMO system using the Almouti space-time codes for higher order PSK and M-ary QAM. MATLAB was used to simulate the system; assuming slow fading Rayleigh channel and additive white Gaussian noise. The simulated performance curves were compared and evaluated with theoretical curves obtained using BER tool on the MATLAB by setting parameters for random generators. The results shows that the technique used do find a place in correcting error rates of QAM system of higher modulation schemes. The model can equally be used not only for the criteria of adaptive modulation but for a platform to design other modulation systems as well.
Online Paper Submission - International Journal of Information Sciences and T...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
Call for Papers - International Journal of Information Sciences and Technique...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
International Journal of Information Sciences and Techniques (IJIST)ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
BRAIN TUMOR MRIIMAGE CLASSIFICATION WITH FEATURE SELECTION AND EXTRACTION USI...ijistjournal
Feature extraction is a method of capturing visual content of an image. The feature extraction is the process to represent raw image in its reduced form to facilitate decision making such as pattern classification. We have tried to address the problem of classification MRI brain images by creating a robust and more accurate classifier which can act as an expert assistant to medical practitioners. The objective of this paper is to present a novel method of feature selection and extraction. This approach combines the Intensity, Texture, shape based features and classifies the tumor as white matter, Gray matter, CSF, abnormal and normal area. The experiment is performed on 140 tumor contained brain MR images from the Internet Brain Segmentation Repository. The proposed technique has been carried out over a larger database as compare to any previous work and is more robust and effective. PCA and Linear Discriminant Analysis (LDA) were applied on the training sets. The Support Vector Machine (SVM) classifier served as a comparison of nonlinear techniques Vs linear ones. PCA and LDA methods are used to reduce the number of features used. The feature selection using the proposed technique is more beneficial as it analyses the data according to grouping class variable and gives reduced feature set with high classification accuracy.
Research Article Submission - International Journal of Information Sciences a...ijistjournal
The International Journal of Information Science & Techniques (IJIST) focuses on information systems science and technology coercing multitude applications of information systems in business administration, social science, biosciences, and humanities education, library sciences management, depiction of data and structural illustration, big data analytics, information economics in real engineering and scientific problems.
This journal provides a forum that impacts the development of engineering, education, technology management, information theories and application validation. It also acts as a path to exchange novel and innovative ideas about Information systems science and technology.
A MEDIAN BASED DIRECTIONAL CASCADED WITH MASK FILTER FOR REMOVAL OF RVINijistjournal
In this paper A Median Based Directional Cascaded with Mask (MBDCM) filter has been proposed, which is based on three different sized cascaded filtering windows. The differences between the current pixel and its neighbors aligned with four main directions are considered for impulse detection. A direction index is used for each edge aligned with a given direction. Minimum of these four direction indexes is used for impulse detection under each masking window. Depending on the minimum direction indexes among these three windows new value to substitute the noisy pixel is calculated. Extensive simulations showed that the MBDCM filter provides good performances of suppressing impulses from both gray level and colored benchmarked images corrupted with low noise level as well as for highly dense impulses. MBDCM filter gives better results than MDWCMM filter in suppressing impulses from highly corrupted digital images.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Recycled Concrete Aggregate in Construction Part II
Colour Image Steganography Based on Pixel Value Differencing in Spatial Domain
1. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
DOI : 10.5121/ijist.2012.2408 83
Colour Image Steganography Based on Pixel Value
Differencing in Spatial Domain
J. K. Mandal and Debashis Das
Department of Computer Science and Engineering,
University of Kalyani, Kalyani,
West Bengal, India
E-mail: jkm.cse@gmail.com , debashisitnsec@gmail.com
ABSTRACT
In a color image every pixel value composed of red, green and blue component and each of which ranges
from 0 to 255 in case of 8-bit representation. In this paper, we have used pixel value differencing (PVD)
method for secret data embedding in each of the component of a pixel in a color image. But when we use
pixel-value differencing (PVD) method as image steganographic scheme, the pixel values in the stego-
image may exceed the range 0~255. We have eliminated this overflow problem of each component pixel.
Furthermore for providing more security, we have used different number of bits in different pixel
components. It would be very difficult to trace how many bits are embedded in a pixel of the stego image.
From the experiments it is seen that the results obtained in proposed method provides better visual quality
of stego-image compared to the PVD method.
Keywords
Steganography, Pixel-value differencing, Pixel component, Stego-image
1. INTRODUCTION
Security measures have become very necessary issue in the age of digital transmission of
information via Internet. Two schemes are used to protect secret messages from being captured
during transmission. One is encryption where the secret information is encoded in another form
by using a secret key before sending, which can only be decoded with secret keys. The most
popular encryption techniques are DES, RSA etc. Other way is steganography which is a
technique of hiding secret information into a cover media or carrier. If the cover media is a digital
image, it is called cover image and the cover image with hidden data is called stego-image.
Steganographic technique can be used in military, commercial, anti-criminal and so on. There are
various steganographic techniques available where a digital image is used as a carrier. The most
common and simplest method is least-significant-bit (LSB) substitution, where the LSB position
of each pixel of the cover image is replaced by one bit of secret data. Wang et al.[7] proposed a
method to embed data by using genetic algorithm to improve the quality of the stego-image.
However, genetic algorithm takes more computational time. Chang et al. Proposed[9] an efficient
dynamic programming strategy to reduce the computational time. Chan and Cheng [11] proposed
to embed data by simple LSB substitution with an optimal pixel adjustment process. Wu and
Tsai[1] proposed a new scheme to hide more data with outstanding quality of stego-image pixel-
2. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
84
value-differencing (PVD) method. Thereafter, based on PVD method various approaches have
been proposed [3,4,5,8,10]. In this paper, a steganographic approach on color images, using PVD
has been proposed. The colour pixel-components may exceed the range 0~255 in the stego image
when applying PVD method. We also have removed this drawback of PVD method here. In the
proposed method a digital colour image has been used as a cover image. It will provide more
security in data hiding and also better stego image quality than Wu-Tsai’s PVD method.
2. REVIEW OF PVD METHOD
In PVD method[2], gray scale image is used as a cover image with a long bit-stream as the secret
data. At first the cover image is partitioned into non-overlapping blocks of two consecutive
pixels, pi and pi+1. From each block the difference value di is calculated by subtracting pi from
pi+1. The set of all difference values may range from -255 to 255. Therefore, |di| ranges from 0 to
255. The blocks with small difference value locates in smooth area where block with large
difference values are the sharp edged area. According to the properties of human vision, eyes can
tolerate more changes in sharp-edge area than smooth area. So, more data can be embedded into
edge area than smooth areas. Therefore, in PVD method a range table has been designed with n
contiguous ranges Rk (where k=1,2,…,n) where the range is 0 to 255. The lower and the upper
bound are denoted as lk and uk respectively, then Rk ∈[lk,uk]. The width of Rk is calculated as
wk=uk-lk+1.wk decides how many bits can be hidden in a pixel block. For security purpose Rk is
kept as a variable, as a result, original range table is required to extract the embedded data.The
embedding algorithm is given as algorithm 1
Algorithm 1:
1. Calculate the difference value di of two consecutive pixels pi and pi+1 for each block in
the cover image. This is given by di=|pi+1-pi |.
2. Compute the optimal range where the difference lies in the range table by using di. This
is calculated as Ri =min(uk- di ), where uk ≥di for all 1≤ k ≤ n
3. Compute the number of bits ‘t’ to be hidden in a pixel block can be defined as t=⎿log2
wi⏌. where wi is the width of the range in which the pixel difference di is belonging
4. Read t bits from binary secret data and convert it into its corresponding decimal value b.
For instance if t=010, then b=2
5. Calculate the new difference value diʹ which is given by diʹ=l i +b
6. Modify the values of pi and p i+1 by the following formula:
(piʹ, p i+1ʹ) = (pi+⎾m/2⏋,pi+1-⎿m/2⏌), if pi≥p i+1 and di'>di
(pi-⎿m/2⏌,pi+1+⎾m/2⏋), if pi<pi+1 and diʹ>di
(pi-⎾m/2⏋),p i+1+⎿m/2⏌), if pi≥p i+1 and d'i≤di
(pi+⎾m/2⏋,p i+1-⎿m/2⏌), if pi<p i+1 and di'≤di
where m=|di'-di|. Now we obtain the pixel pair (pi',pi+1') after embedding the secret data into pixel
pair (pi,pi+1). Repeat step 1-6 until all secret data are embedded into the cover image. Hence we
get the stego-image.
When extracting the hidden information from the stego-image, original range table is required. At
first partition the stego-image into pixel blocks , containing two consecutive non-overlapping
pixels each. Calculate the difference value for each block as di'=|pi'-p i+1'|.Then find the optimum
range Ri of d'i . Then b' is obtained by subtracting li from di'. Convert b' into its corresponding
binary of ‘t’ bits, where t=⎿log2 wi ⏌. These t bits are the hidden secret data obtained from the
pixel block(pi',pi+1').
3. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
85
3. PROPOSED METHOD
Every pixel in a colour image composed of three colours (channels) i.e. Red, Green and Blue. So,
every pixel contains 24 bits (for 8-bit representation) where 8 bits for red component, 8 bits for
green and 8 bits for blue component in a pixel, shown in Fig.1. In the proposed technique, all the
three components have been used for data embedding. First, we have separated each colour
component from a pixel and get three separate M*N matrix, one for each component colour,
where the original image size is M*N. Now, apply pixel value differencing method for data
hiding in each matrix separately, but in a sequencing manner. First embed bits in 1st
pixel block
(two consecutive non-overlapping pixels) of the red component matrix, then in 1st
block of green
component matrix and lastly in blue component matrix, then again 2nd
block of red matrix and so
on. In this way secret data is embedded into the total image. Further we have embedded different
number of bits for different component pixel blocks for increasing security as well as improving
the visual quality of the stego-image, shown in Fig.2.
Fig.1 Components of a colour pixel
Difference Range Table
G(max 3bits)
R(max 5 bits)
B(max 7 bits)
Fig.2 Number of bits can be hidden in various components
In addition, it is seen that pixel values in the stego image may exceed the range 0~255 on
applying PVD which is not desirable as it may lead to improper visualisation of the stego image.
In this section we introduce a technique to overcome this problem. In the proposed method we
have used the original PVD method to embed secret data. If any pixel value exceeds the range (0
to 255), then check the bit-stream ‘t’ to be hidden. If MSB(most significant bit) of the selected
bit stream ’t’ is 1 then we embed one less number of bits, where MSB position is discarded from
t; otherwise the bit number of hidden data depends on wi . For instance, if pixel value exceeds the
range and selected bit-stream t=101, then set t=01 and embed it. If it is seen that the pixel value
again exceeding range, then embed the value at one pixel, rather than both pixels(of the pixel
block), which will not exceed the range after embedding; where the other pixel is kept
unchanged. It will keep the pixel values within the range because both pixels of a block cannot
exceed at the same time as per the PVD method by Wu and Tsai. Keep the information within
each block, whether one less bit is embedded or not, as overhead. The embedding algorithm is
presented in section 3.1. Fig.3 shows the block diagram of the embedding algorithm.
3.1. Embedding Algorithm
Step 1: Separate the colour image into three component colour matrix and apply the following
steps on each of them sequentially i.e. apply following steps on 1st
pixel block of RED
Three components of a colour pixel One true colour pixel
RED(226) GREEN(137) BLUE(125)
(11100010) (10001001) (01111101)
(226 , 137 , 125)
(11100010 , 10001001 , 01111101)
0~7 8~15 16~31 32~63 64~127 128~255
4. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
86
matrix, then 1st
block of GREEN matrix and finally on BLUE matrix, then started from
2nd
block of each matrix and so on.
Step 2: Calculate the difference value di for each block of two consecutive non-overlapping
pixels pi and pi+1 , is given by di=|pi-pi+1|.
Step 3: Find optimal range Ri for the di such that Ri =min(ui-di) , where ui≥di .Then Ri ∈[li , ui] is
the optimum range where the difference lies.
Step 4: Compute the amount of secret data bits t from the width wi of the optimum range, can
be defined as t=⎿log2 wi⏌.
Step 5: For RED matrix, if t ≤ 5 then execute the next steps; otherwise no embedding in the
block
For GREEN matrix, if t ≤ 3 then execute the next steps; otherwise no embedding
For Blue matrix execute the following steps.
Step 6: Read t bits and convert it into a decimal value b. Then calculate the new difference value
by the formula di'=li+b .
Step 7: Now, calculate the pixel values after embedding t bits (pi' , pi+1')by original PVD method.
Step 8: Check the embedded pixel values whether it exceed the gray-level range or not . If it
exceeds then check the embedded bit-stream t . Otherwise go to step 9.
Step 8.1: If the left most position of the bit-stream is 1 then select ‘t’ by discarding one bit from
its left most position. Convert ‘t’ bits into its corresponding decimal value b and find
new difference value as di'=li+b . Otherwise do not discard any bit from ‘t’ and calculate
di' .
Step 8.2: Calculate new pixel values (pi' , pi+1') using original PVD method and check again if it
is in the gray range. If it is in the range then go to step 9.Otherwise do the following :
(pi' , pi+1')=(pi-m , pi+1), if pi+1 ≥ pi and pi+1 crossing the upper range(i.e 255) ;
(pi ', pi+1')=(pi , pi+1-m), if pi+1<pi and pi crossing the upper range(i.e 255) ;
(pi' , pi+1')=(pi , pi+1+m), if pi+1≥pi and pi crossing the lower range(i.e 0);
(pi ', pi+1')=(pi+m , pi+1), if pi+1<pi and pi+1 crossing the lower range(i.e 0) .
where m=|di'-di| .
Step 9: Now, the pixel block (pi , pi+1) is replaced by (pi' , pi+1').
Step 10: To keep the information whether ‘t’ bits or ‘t-1’ bits has been embedded, do the
following for each modified block :
Step 10.1:
If no bit has been discarded then do the following:
LSB of P'i LSB of P'i+1 then do
5. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
87
i) 0 0 P'i+1 +1
ii) 0 1
a) P'i+1 <255 and P'I ≥ 0 P'i+1 +1
b) P'i >0 and P'i+1 =255 P'i-2 and P'i+1 -1
c) P'i=0 , P'i+1=255 P'i +1
iii) 1 0 P'i -1
iv) 1 1 P'i -1
Step 10.2:
One bit has been discarded
LSB of P'i LSB of P'i+1 then do
i) 0 0 P'i +1
ii) 0 1 P'i +1
iii) 1 0
a) P'i+1 >0 and P'i ≤ 255 P'i+1 -1
b) P'i <255 and P'i+1 =0 P'i+2 and P'i+1+1
iv) 1 1 P'i+1 -1
Step 11: Now we get the stego blocks and hence the stego image.
3.2. Extraction Algorithm
Figure 3 shows the block diagram of the extraction algorithm. The steps used for extracting the
hidden data are as follows :
Step 1: Divide the stego image into three component matrix RED, GREEN and BLUE and
execute the following steps for each pixel block, consist of two consecutive non-overlapping
pixels, of RED, GREEN, BLUE respectively i.e. extract bits from one stego pixel at a time.
Step 2: Check the LSB positions of Pi (first pixel of the block) for each block and do the
following :
LSB of Pi Convert it as
0 Pi +1
1 Pi -1
6. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
88
Step 3: Now calculate the difference value di of two consecutive pixels of each block by using the
formula di=|pi-pi+1| .
Step 4: Find the appropriate range Ri for the difference di.
Step 5: Calculate the number of bits hidden into each block by the formula t=⎿log2 wi⏌, wi is
the width of the optimal range Ri .
Step 6: If operating on RED block and ‘t’ ≤ 3 then execute following steps; otherwise no
extraction
If operating on GREEN block and ‘t’ ≤ 5 then execute following steps; otherwise no
extraction
If operating on BLUE block and ‘t’ ≤ 7 then execute the following steps
Step 7: Extract ‘t’ bits, by the extracting method of original PVD.
Step 8: Check the LSB of Pi . If it is 1, replace the MSB position of extracted ‘t’ bits with ‘1’.
Otherwise do nothing.
7. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
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Fig. 3 Block diagram of embedding and extraction algorithm
8. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
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4. EXPERIMENTAL RESULTS
The proposed scheme hides secret data into a colour image using pixel value differencing method
but various bits in different channels or colour components. Also the problem of overshooting
0~255 range for each component pixels, occurs in PVD, has been removed here. This scheme
results better visual quality of the stego image. To prove the proposal practically we have used C
programming language to implement our scheme and Wu-Tsai’s PVD scheme. We have also
shown the management of pixel value range for a gray scale cover image, where the capacity
remains same with original PVD method. The range table width used here are wi ={ 8, 8, 16, 32,
64, 128 }.We have used cover images of size 512*512 and hide a large bit stream as the secret
information. We have used the Peak-Signal-to-Noise ratio (PSNR) to evaluate the quality of
stego-image. The experimental results are shown in Fig. 4 for colour image and Fig. 5 showing
the results of gray images. A table of results for colour images is given in Table 1 depicting the
capacity of hidden message and the PSNR values. The comparison, of message payload and
PSNR value, between proposed method (in both gray image and colour image) and original PVD
method is shown in Table 2. The PSNR value and payload capacity of each stego-image is given
as average value by executing 100 rounds using standard digital images where the hidden
information are different.
5. ANALYSES AND DISCUSSION
From the experimental results, using colour image as cover media, we can see that PSNR values
are increasing for every stego image compared to original PVD method. In a colour image, the
contribution of the component colours (red, green or blue) of a pixel is different. Green
component contributes 59% where red component contributes 30% and blue component provide
11% contribution to make a colour pixel. So, we have embedded more bits to blue channels and
lower bits to the green and red components. This results less distortion of the pixels in stego
image. Also it provides more security because different number of bits has been hidden in
different channels of a pixel, so is hard to trace how many bits are hidden within a pixel. On the
other hand, according to the proposed method, if pixel component value exceeds 0~255 ranges on
embedding, one MSB bit is discarded from the selected bit-stream to be hidden. So, decimal
value of the reduced bits will be half or less than half. As a result the distortion of the pixel value
in the stego-image will be less. Also It should be noted that whether the pixel exceeds range or
not, we have to keep the information in every component pixel block by adding or subtracting 0,
1, or 2. But this has no remarkable effect for reducing PSNR value for colour image.
In case of gray scale cover image, capacity remains same for the proposed method as in original
PVD method. PSNR values have been changing between -0.62 to +0.32 dB. For gray image
pixels, keeping of overhead information affects the PSNR to reduce in some cases.
9. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
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Fig.4. Cover images and their corresponding stego images
Cover image Stego image Cover image Stego image
Fig.5. Cover images and corresponding Stego images for gray scale image
Table 1: Experimental results of the proposed method
Cover image
(512 512
Proposed method
Capacity PSNR
Lena 145787 42.26
Baboon 144916 38.44
Jet 145648 42.60
Pepper 145995 42.28
Girl 144285 42.80
House 145374 41.41
Splash 146732 42.86
Sailboat 143278 40.66
Capacity in Bytes and PSNR in dB and Cover images of size 512*512
Table 2: Comparison of results of the proposed and Wu and Tsai’s method
Cover image
(512 512
Wu and Tsai’s
method
Payload PSNR
Proposed method
Gray Image Colour Image
Payload PSNR Payload PSNR
Lena 1.56 41.70 1.56 40.61 1.48 42.26
Baboon 1.75 36.86 1.75 36.67 1.47 38.44
Jet 1.55 41.31 1.55 40.94 1.48 42.60
Pepper 1.55 40.55 1.55 40.61 1.48 42.28
Payload in bpB and PSNR in dB and Cover images of size 512*512 .
10. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
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6. CONCLUSIONS
In this paper, we have discussed a steganographic method for data hiding by using pixel value
differencing in colour images which also guarantees that no pixel value will exceed the range 0 to
255 in stego-image. We have shown the pixel range overflow management also for gray scale
images. We have used original PVD method where pixel value does not cross the range,
elsewhere proposed method has been used for embedding data. Proposed scheme on colour
images gives more security than the original PVD used in grey images and also provides better
visual quality of stego-image. Furthermore, proposed method extracts the hidden secret message
efficiently without using the original cover image.
ACKNOWLEDGEMENTS
The authors express gratitude to the Department of Computer Science and Engineering,
University of Kalyani and the PURSE scheme of DST, Govt. of India, under which the research
has been carried out.
REFERENCES
[1] J.K. Mandal, Debashis Das “Steganography Using Adaptive Pixel Value Differencing(APVD) for
Gray Images through Exclusion of Underflow/Overflow ”, Computer Science Information Series,
ISBN : 978-1-921987-03-8, pp. 93-102, 2012.
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differencing and LSB replacement method”, IEEE Proceedings on Vision, Image and Signal
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[3] Schneier B.:'Applied cryptography'(John Wiley Sons, New York, 1996, 2nd
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11. International Journal of Information Sciences and Techniques (IJIST) Vol.2, No.4, July 2012
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Authors
Jyotsna Kumar Mandal, M.Tech(Computer Science, University of Calcutta),
Ph.D.(Engg. , Jadavpur University) in the field of Data Compression and Error
Correction Techniques, Professor in Computer Science and Engineering, University of
Kalyani, India. Life member of Computer Society of India since 1992 and life member
of Cryptology Research Society of India. Dean Faculty of Engineering, Technology
and Management, working in the field of Network Security, Steganography, Remote
Sensing GIS Application, Image Processing. 25 years of teaching and research
experiences. Eight scholars awarded Ph.D., one submitted and eight are pursuing. Total
number of publications is more than two hundred and thirty in addition of publication of five books from
LAP, Germany .
Debashis Das pursuing his M. Tech. in Computer Science and Engineering from
University of Kalyani, under the Department of Computer Science and Engineering.
Received his B. Tech degree in Information Technology in 2009. He has two public
ations in the in ternational conference proceedings.