Encryption is used to securely transmit data in open networks. Each type of data has its own features. With the rapid growth of internet, security of digital images has become more and more important. Therefore different techniques should be used to protect confidential image data from unauthorized access. In this paper an encryption technique based on elliptic curves for securing images to transmit over public channels will be proposed. Encryption and decryption process are given in details with an example. The comparative study of the proposed scheme and the existing scheme is made. Our proposed algorithm is aimed at better encryption of all types of images even ones with uniform background and makes the image encryption scheme more secure. The output encrypted images reveal that the proposed method is robust.
Image confusion and diffusion based on multi-chaotic system and mix-columnjournalBEEI
In this paper, a new image encryption algorithm based on chaotic cryptography was proposed. The proposed scheme was based on multiple stages of confusion and diffusion. The diffusion process was implemented twice, first, by permuting the pixels of the plain image by using an Arnold cat map and, the second time by permuting the plain image pixels via the proposed permutation algorithm. The confusion process was performed many times, by performing the XOR operation between the two resulted from permuted images, subtracted a random value from all pixels of the image, as well as by implementing the mix column on the resulted image, and by used the Lorenz key to obtain the encrypted image. The security analysis tests that used to exam the results of this encryption method were information entropy, key space analysis, correlation, histogram analysis UACI, and NPCR have shown that the suggested algorithm has been resistant against different types of attacks.
This paper presents an FPGA-based algorithm for moving object detection from video for traffic surveillance. The algorithm uses background subtraction, edge detection and shadow detection techniques. Background subtraction involves selective and non-selective updating to improve sensitivity. Edge detection helps find object boundaries while shadow detection removes falsely detected pixels from shadows. The algorithm is implemented using VHDL on a Spartan-6 FPGA board. Experimental results show the algorithm can accurately detect moving vehicles in different lighting conditions with low power consumption, making it suitable for traffic monitoring applications.
A Novel GA-SVM Model For Vehicles And Pedestrial Classification In Videosijtsrd
The paper presents a novel algorithm for object classification in videos based on improved support vector machine (SVM) and genetic algorithm. One of the problems of support vector machine is selection of the appropriate parameters for the kernel. This has affected the accuracy of the SVM over the years. This research aims at optimizing the SVM Radial Basis kernel parameters using the genetic algorithm. Moving object classification is a requirement in smart visual surveillance systems as it allows the system to know the kind of object in the scene and be able to recognize the actions the object can perform. This paper presents an GA-SVM machine learning approach for real time object classification in videos. Radial distance signal features are extracted from the silhouettes of object detected in videos. The radial distance signals features are then normalized and fed into the GA-SVM model. The classification rate of 99.39% is achieved with the genetically trained SVM algorithm while 99.1% classification accuracy is achieved with the normal SVM. A comparison of this classifier with some other classifiers in terms of classification accuracy shows a better performance than other classifiers such as the normal SVM, Artificial neural network (ANN), Genetic Artificial neural network (GANN), K-nearest neighbor (K-NN) and K-Means classifiers. Akintola Kolawole G."A Novel GA-SVM Model For Vehicles And Pedestrial Classification In Videos" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017, URL: http://www.ijtsrd.com/papers/ijtsrd109.pdf http://www.ijtsrd.com/computer-science/artificial-intelligence/109/a-novel-ga-svm-model-for-vehicles-and-pedestrial-classification-in-videos/akintola-kolawole-g
MULTIPLE HUMAN TRACKING USING RETINANET FEATURES, SIAMESE NEURAL NETWORK, AND...IAEME Publication
Multiple human tracking based on object detection has been a challenge due to its
complexity. Errors in object detection would be propagated to tracking errors. In this
paper, we propose a tracking method that minimizes the error produced by object
detector. We use RetinaNet as object detector and Hungarian algorithm for tracking.
The cost matrix for Hungarian algorithm is calculated using the RetinaNet features,
bounding box center distances, and intersection of unions of bounding boxes. We
interpolate the missing detections in the last step. The proposed method yield 43.2
MOTA for MOT16 benchmark
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Semantic Video Segmentation with Using Ensemble of Particular Classifiers and...ITIIIndustries
A new approach based on the use of a deep neural network and an ensemble of particular classifiers is proposed. This approach is based on use of the novel block of fuzzy generalization for combines classes of objects into semantic groups, each of which corresponds to one or more particular classifiers. As result of processing, the sequence of frames is converted into the annotation of the event occurring in the video for a certain time interval
ALGORITHMIC AND ARCHITECTURAL OPTIMIZATION OF A 3D RECONSTRUCTION MEDICAL IMA...IJCSEIT Journal
This document summarizes an optimization of a 3D reconstruction algorithm called Marching Cubes for hardware implementation on an FPGA. It describes:
1) The Marching Cubes algorithm which generates a triangular mesh from segmented medical images and its repetitive nature.
2) The AAA methodology and SynDEx-IC tool used to specify the algorithm graph and optimize for the FPGA architecture through factorization and defactorization.
3) The optimized implementation generated by SynDEx-IC including a data path with calculation operators and memory, and a control path to coordinate factorization frontiers.
Colour Image Segmentation Using Soft Rough Fuzzy-C-Means and Multi Class SVM ijcisjournal
Color image segmentation algorithms in the literature segment an image on the basis of color, texture, and
also as a fusion of both color and texture. In this paper, a color image segmentation algorithm is proposed
by extracting both texture and color features and applying them to the One-Against-All Multi Class Support
Vector Machine classifier for segmentation. A novel Power Law Descriptor (PLD) is used for extracting
the textural features and homogeneity model is used for obtaining the color features. The Multi Class SVM
is trained using the samples obtained from Soft Rough Fuzzy-C-Means (SRFCM) clustering. Fuzzy set
based membership functions capably handle the problem of overlapping clusters. The lower and upper
approximation concepts of rough sets deal well with uncertainty, vagueness, and incompleteness in data.
Parameterization tools are not a prerequisite in defining Soft set theory. The goodness aspects of soft sets,
rough sets and fuzzy sets are incorporated in the proposed algorithm to achieve improved segmentation
performance. The Power Law Descriptor used for texture feature extraction has the advantage of being
dealt in the spatial domain thereby reducing computational complexity. The proposed algorithm is
comparable and achieved better performance compared with the state of the art algorithms found in the
literature.
Image confusion and diffusion based on multi-chaotic system and mix-columnjournalBEEI
In this paper, a new image encryption algorithm based on chaotic cryptography was proposed. The proposed scheme was based on multiple stages of confusion and diffusion. The diffusion process was implemented twice, first, by permuting the pixels of the plain image by using an Arnold cat map and, the second time by permuting the plain image pixels via the proposed permutation algorithm. The confusion process was performed many times, by performing the XOR operation between the two resulted from permuted images, subtracted a random value from all pixels of the image, as well as by implementing the mix column on the resulted image, and by used the Lorenz key to obtain the encrypted image. The security analysis tests that used to exam the results of this encryption method were information entropy, key space analysis, correlation, histogram analysis UACI, and NPCR have shown that the suggested algorithm has been resistant against different types of attacks.
This paper presents an FPGA-based algorithm for moving object detection from video for traffic surveillance. The algorithm uses background subtraction, edge detection and shadow detection techniques. Background subtraction involves selective and non-selective updating to improve sensitivity. Edge detection helps find object boundaries while shadow detection removes falsely detected pixels from shadows. The algorithm is implemented using VHDL on a Spartan-6 FPGA board. Experimental results show the algorithm can accurately detect moving vehicles in different lighting conditions with low power consumption, making it suitable for traffic monitoring applications.
A Novel GA-SVM Model For Vehicles And Pedestrial Classification In Videosijtsrd
The paper presents a novel algorithm for object classification in videos based on improved support vector machine (SVM) and genetic algorithm. One of the problems of support vector machine is selection of the appropriate parameters for the kernel. This has affected the accuracy of the SVM over the years. This research aims at optimizing the SVM Radial Basis kernel parameters using the genetic algorithm. Moving object classification is a requirement in smart visual surveillance systems as it allows the system to know the kind of object in the scene and be able to recognize the actions the object can perform. This paper presents an GA-SVM machine learning approach for real time object classification in videos. Radial distance signal features are extracted from the silhouettes of object detected in videos. The radial distance signals features are then normalized and fed into the GA-SVM model. The classification rate of 99.39% is achieved with the genetically trained SVM algorithm while 99.1% classification accuracy is achieved with the normal SVM. A comparison of this classifier with some other classifiers in terms of classification accuracy shows a better performance than other classifiers such as the normal SVM, Artificial neural network (ANN), Genetic Artificial neural network (GANN), K-nearest neighbor (K-NN) and K-Means classifiers. Akintola Kolawole G."A Novel GA-SVM Model For Vehicles And Pedestrial Classification In Videos" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017, URL: http://www.ijtsrd.com/papers/ijtsrd109.pdf http://www.ijtsrd.com/computer-science/artificial-intelligence/109/a-novel-ga-svm-model-for-vehicles-and-pedestrial-classification-in-videos/akintola-kolawole-g
MULTIPLE HUMAN TRACKING USING RETINANET FEATURES, SIAMESE NEURAL NETWORK, AND...IAEME Publication
Multiple human tracking based on object detection has been a challenge due to its
complexity. Errors in object detection would be propagated to tracking errors. In this
paper, we propose a tracking method that minimizes the error produced by object
detector. We use RetinaNet as object detector and Hungarian algorithm for tracking.
The cost matrix for Hungarian algorithm is calculated using the RetinaNet features,
bounding box center distances, and intersection of unions of bounding boxes. We
interpolate the missing detections in the last step. The proposed method yield 43.2
MOTA for MOT16 benchmark
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Semantic Video Segmentation with Using Ensemble of Particular Classifiers and...ITIIIndustries
A new approach based on the use of a deep neural network and an ensemble of particular classifiers is proposed. This approach is based on use of the novel block of fuzzy generalization for combines classes of objects into semantic groups, each of which corresponds to one or more particular classifiers. As result of processing, the sequence of frames is converted into the annotation of the event occurring in the video for a certain time interval
ALGORITHMIC AND ARCHITECTURAL OPTIMIZATION OF A 3D RECONSTRUCTION MEDICAL IMA...IJCSEIT Journal
This document summarizes an optimization of a 3D reconstruction algorithm called Marching Cubes for hardware implementation on an FPGA. It describes:
1) The Marching Cubes algorithm which generates a triangular mesh from segmented medical images and its repetitive nature.
2) The AAA methodology and SynDEx-IC tool used to specify the algorithm graph and optimize for the FPGA architecture through factorization and defactorization.
3) The optimized implementation generated by SynDEx-IC including a data path with calculation operators and memory, and a control path to coordinate factorization frontiers.
Colour Image Segmentation Using Soft Rough Fuzzy-C-Means and Multi Class SVM ijcisjournal
Color image segmentation algorithms in the literature segment an image on the basis of color, texture, and
also as a fusion of both color and texture. In this paper, a color image segmentation algorithm is proposed
by extracting both texture and color features and applying them to the One-Against-All Multi Class Support
Vector Machine classifier for segmentation. A novel Power Law Descriptor (PLD) is used for extracting
the textural features and homogeneity model is used for obtaining the color features. The Multi Class SVM
is trained using the samples obtained from Soft Rough Fuzzy-C-Means (SRFCM) clustering. Fuzzy set
based membership functions capably handle the problem of overlapping clusters. The lower and upper
approximation concepts of rough sets deal well with uncertainty, vagueness, and incompleteness in data.
Parameterization tools are not a prerequisite in defining Soft set theory. The goodness aspects of soft sets,
rough sets and fuzzy sets are incorporated in the proposed algorithm to achieve improved segmentation
performance. The Power Law Descriptor used for texture feature extraction has the advantage of being
dealt in the spatial domain thereby reducing computational complexity. The proposed algorithm is
comparable and achieved better performance compared with the state of the art algorithms found in the
literature.
11.secure compressed image transmission using self organizing feature mapsAlexander Decker
This document summarizes a research paper that proposes a method for secure compressed image transmission using self-organizing feature maps. The method involves compressing images using SOFM-based vector quantization, entropy coding the results, and encrypting the compressed data using a scrambler before transmission. Simulation results show the method achieves a compression ratio of up to 38:1 while providing security, outperforming JPEG compression by up to 1 dB. The paper presents the technical details and evaluation of the proposed secure image transmission system.
Double layer security using visual cryptography and transform based steganogr...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Analysis of image storage and retrieval in graded memoryeSAT Journals
Abstract An approach to storing and retrieving static images using multilayer Hopfield neural network is analyzed. Here, the Hopfield network is used as a memory, which stores images in predefined resolution. During the image retrieval, down sampled version of the stored image is provided as the query mage, The memory initially gives out a coarse image. The finer details of the image are synthesized later by using this coarse output image. This coarse output image is fed as the input to the memory again. The output this time will be better than the output that was got initially. The output of the memory becomes better and better as the time progresses. We call this memory a graded memory. Here the work proposes various models of the graded memory using multilayer Hopfield neural network, analyses the effectiveness of this memory with parameters like MSE, RMSE and PSNR. Keywords: Hopfield network, graded memory, image storage, image retrieval.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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.
SECURE OMP BASED PATTERN RECOGNITION THAT SUPPORTS IMAGE COMPRESSIONsipij
In this paper, we propose a secure Orthogonal Matching Pursuit (OMP) based pattern recognition scheme that well supports image compression. The secure OMP is a sparse coding algorithm that chooses atoms sequentially and calculates sparse coefficients from encrypted images. The encryption is carried out by using a random unitary transform. The proposed scheme offers two prominent features. 1) It is capable of
pattern recognition that works in the encrypted image domain. Even if data leaks, privacy can be maintained because data remains encrypted. 2) It realizes Encryption-then-Compression (EtC) systems, where image encryption is conducted prior to compression. The pattern recognition can be carried out using a
few sparse coefficients. On the basis of the pattern recognition results, the scheme can compress selected images with high quality by estimating a sufficient number of sparse coefficients. We use the INRIA dataset to demonstrate its performance in detecting humans in images. The proposal is shown to realize human detection with encrypted images and efficiently compress the images selected in the image recognition stage.
IMPROVING OF ARTIFICIAL NEURAL NETWORKS PERFORMANCE BY USING GPU’S: A SURVEYcsandit
This document provides a survey of improving the performance of artificial neural networks (ANNs) through parallel programming on GPUs. It discusses different ANN training strategies that can be parallelized, such as perceptrons, support vector machines, and spiking neural networks. GPUs provide significant speed advantages over CPUs for ANN training. The document reviews various studies that have implemented ANNs using GPUs and FPGAs, finding that GPUs reduce training time compared to CPUs, especially for algorithms involving large matrix operations like support vector machines. Spiking neural networks are better suited to FPGAs or custom circuits due to their complex temporal dynamics. The document concludes that GPUs are generally the best approach for ANN parallelization, but the
Improving of artifical neural networks performance by using gpu's a surveycsandit
In this paper we study the improvement in the performance of Artificial Neural Networks (ANN)
by using parallel programming in GPU or FPGA architectures. It is well known that ANN can
be parallelized according to particular characteristics of the training algorithm. We discuss
both approaches: the software (GPU) and the Hardware (FPGA). Different training strategies
are discussed: the Perceptron training unit, the Support Vector Machines (SVM) and Spiking
Neural Networks (SNN). The different approaches are evaluated by the training speed and
performance. On the other hand, algorithms were coded by authors in the hardware, like Nvidia
card, FPGA or sequential circuits that depends on methodology used, to compare learning time
with between GPU and CPU. Also, the main applications were made for recognition pattern,
like acoustic speech, odor and clustering According to literature, GPU has a great advantage
compared to CPU, this in the learning time except when it implies rendering of images, despite
several architectures of Nvidia cards and CPU’s. Also, in the survey we introduce a brief
description of the types of ANN and its techniques of execution to be related with results of
researching.
Design a New Image Encryption using Fuzzy Integral Permutation with Coupled C...IJORCS
This document proposes a new image encryption algorithm combining DNA sequence addition and coupled chaotic maps. The algorithm has two parts: 1) A DNA sequence matrix is obtained by encoding image pixels and divided into blocks that are added using Sugeno fuzzy integral, 2) The modified color components are encrypted using coupled two-dimensional piecewise nonlinear chaotic maps to strengthen security. Experimental results on image databases show the algorithm effectively protects digital image security over the internet.
Performance Evaluation of Object Tracking Technique Based on Position VectorsCSCJournals
This document presents a novel algorithm for object tracking in video frames based on position vectors. The algorithm first extracts position vectors for the object in the first frame. It then tracks the object across subsequent frames by cropping each new frame into blocks based on shifted position vectors and performing block matching between frames using feature vectors extracted by discrete wavelet transform (DWT) or dual tree complex wavelet transform (DTCWT). Experimental results on video sequences show the algorithm using DTCWT achieves higher tracking precision (95%) compared to DWT (92%). The algorithm is computationally efficient and can track multiple moving and still objects.
The code reads in a grayscale image, calculates its histogram using a specified number of bins, and plots the histogram. It also determines the maximum and minimum pixel values in the image and uses these to rescale the pixel values before calculating the histogram.
Robust Adaptive Threshold Algorithm based on Kernel Fuzzy Clustering on Image...cscpconf
The document presents a robust adaptive threshold algorithm based on kernel fuzzy clustering for image segmentation. It proposes using kernel fuzzy c-means clustering (KFCM) to generate adaptive thresholds for segmenting images. KFCM computes fuzzy membership values for pixels to cluster them. The algorithm was tested on MR brain images and showed good performance in detecting large and small objects while also enhancing low contrast images. Experimental results demonstrated the efficiency and accuracy of combining an adaptive threshold algorithm with KFCM for medical image segmentation.
Data Hiding Method With High Embedding Capacity CharacterCSCJournals
Recently, the data hiding method based on the high embedding capacity by using improved EMD method was proposed by Kuo et al.[6]. They claimed that their scheme can not only hide a great deal of secret data but also keep high safety and good image quality. However, in their scheme, the sender and the receiver must share the synchronous random secret seed before they transmit the stego-image each other. Otherwise, they can not recover the correct secret information from the stego-image. In this paper we propose an improved scheme based on EMD and LSB matching method to overcome the above problem, in other words, the sender does not share the synchronous random secret seed the receiver before the stego-image is transmitted. Observing the experimental results, they show that our proposed scheme acquires high embedding capacity and acceptable stego-image quality.
Performance boosting of discrete cosine transform using parallel programming ...IAEME Publication
This document summarizes a paper that proposes using parallel programming techniques to improve the performance of the discrete cosine transform (DCT) algorithm. It describes implementing both thread-level parallelism by distributing image blocks across multiple processor cores, and vector-level parallelism by performing SIMD operations within each core using AVX instructions. The proposed methodology uses Cilk Plus to enable parallelization at both the thread and vector levels. It is estimated that this multi-level parallel approach could theoretically provide a speedup of up to 32 times compared to a serial scalar implementation.
Black-box modeling of nonlinear system using evolutionary neural NARX modelIJECEIAES
Nonlinear systems with uncertainty and disturbance are very difficult to model using mathematic approach. Therefore, a black-box modeling approach without any prior knowledge is necessary. There are some modeling approaches have been used to develop a black box model such as fuzzy logic, neural network, and evolution algorithms. In this paper, an evolutionary neural network by combining a neural network and a modified differential evolution algorithm is applied to model a nonlinear system. The feasibility and effectiveness of the proposed modeling are tested on a piezoelectric actuator SISO system and an experimental quadruple tank MIMO system.
TRANSFER LEARNING BASED IMAGE VISUALIZATION USING CNNijaia
Image classification is a popular machine learning based applications of deep learning. Deep learning techniques are very popular because they can be effectively used in performing operations on image data in large-scale. In this paper CNN model was designed to better classify images. We make use of feature extraction part of inception v3 model for feature vector calculation and retrained the classification layer with these feature vector. By using the transfer learning mechanism the classification layer of the CNN model was trained with 20 classes of Caltech101 image dataset and 17 classes of Oxford 17 flower image dataset. After training, network was evaluated with testing dataset images from Oxford 17 flower dataset and Caltech101 image dataset. The mean testing precision of the neural network architecture with Caltech101 dataset was 98 % and with Oxford 17 Flower image dataset was 92.27 %.
Human Action Recognition using Contour History Images and Neural Networks Cla...IRJET Journal
This document proposes a new method for human action recognition using contour history images extracted from silhouettes, tracking of the body's center movement, and the relative dimensions of the bounding box containing each contour history image. Features are extracted and reduced using three different methods: dividing the contour history images into rectangles, a shallow autoencoder neural network, and a deep autoencoder neural network. The reduced features are classified using a neural network classifier. The proposed method achieved a recognition rate of 98.9% on a standard human action dataset, demonstrating its potential for real-time human action recognition applications.
Real-time Multi-object Face Recognition Using Content Based Image Retrieval (...IJECEIAES
Face recognition system in real time is divided into three processes, namely feature extraction, clustering, detection, and recognition. Each of these stages uses different methods, Local Binary Pattern (LBP), Agglomerative Hierarchical Clustering (AHC) and Euclidean Distance. Multi-face image search using Content Based Image Retrieval (CBIR) method. CBIR performs image search by image feature itself. Based on real time trial results, the accuracy value obtained is 61.64%.
GSM technology is used to monitor the different parameters of an ICU patient remotely and also control over medicine dosage is provided. Measurements of vital signs and behavioral patterns can be translated into accurate predictors of health risk ,even at an early stage and can be combined with alarm triggering systems in order to initiate the appropriate actions. The conventional methods including wet adhesive Ag/AgCl electrodes for HR and HRV, the capnograph device for respiratory status and pulse oximetry for oxyhemoglobin saturation provide excellent signals but are expensive, troublesome and inconvenient. A method to monitor physiological information based on GSM offers a new means for health monitoring. In this paper, we review the latest developments in monitoring and discuss the challenges and future directions for this field.
Supercapacitors or EDLCs (i.e. electric double-layer capacitors) or ultra-capacitors are becoming increasingly popular as alternatives for the conventional and traditional battery sources. This brief overview focuses on the different types of supercapacitors, the relevant quantitative modeling areas and the future of supercapacitor research and development. Supercapacitors may emerge as the solution for many application-specific power systems. Especially, there has been great interest in developing supercapacitors for electric vehicle hybrid power systems, pulse power applications, as well as back-up and emergency power supplies. Because of their flexibility, however, supercapacitors can be adapted to serve in roles for which electrochemical batteries are not as well suited. Also, supercapacitors have some intrinsic characteristics that make them ideally suited to specialized roles and applications that complement the strengths of batteries. In particular, supercapacitors have great potential for applications that require a combination of high power, short charging time, high cycling stability and long shelf life. So, let’s just begin the innovative journey of these near future of life-long batteries that can charge up almost anything and everything within a few seconds!
In this study, trans-consonantal vowel-to-vowel anticipatory coarticulation in Chinese is investigated. The target words are in the form of 'ba.bV2', and the subjects are eight native speakers of standard Chinese. Vowel formants are examined at the offset, middle and onset points of the target vowel. Results show that trans-segmental coarticulation exists in Chinese, especially at the offset point of the target vowel. Coarticulation is more likely to occur on F2, and in Chinese, coarticulatory effect does not extend to the onset point of the vowel.
11.secure compressed image transmission using self organizing feature mapsAlexander Decker
This document summarizes a research paper that proposes a method for secure compressed image transmission using self-organizing feature maps. The method involves compressing images using SOFM-based vector quantization, entropy coding the results, and encrypting the compressed data using a scrambler before transmission. Simulation results show the method achieves a compression ratio of up to 38:1 while providing security, outperforming JPEG compression by up to 1 dB. The paper presents the technical details and evaluation of the proposed secure image transmission system.
Double layer security using visual cryptography and transform based steganogr...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Analysis of image storage and retrieval in graded memoryeSAT Journals
Abstract An approach to storing and retrieving static images using multilayer Hopfield neural network is analyzed. Here, the Hopfield network is used as a memory, which stores images in predefined resolution. During the image retrieval, down sampled version of the stored image is provided as the query mage, The memory initially gives out a coarse image. The finer details of the image are synthesized later by using this coarse output image. This coarse output image is fed as the input to the memory again. The output this time will be better than the output that was got initially. The output of the memory becomes better and better as the time progresses. We call this memory a graded memory. Here the work proposes various models of the graded memory using multilayer Hopfield neural network, analyses the effectiveness of this memory with parameters like MSE, RMSE and PSNR. Keywords: Hopfield network, graded memory, image storage, image retrieval.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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.
SECURE OMP BASED PATTERN RECOGNITION THAT SUPPORTS IMAGE COMPRESSIONsipij
In this paper, we propose a secure Orthogonal Matching Pursuit (OMP) based pattern recognition scheme that well supports image compression. The secure OMP is a sparse coding algorithm that chooses atoms sequentially and calculates sparse coefficients from encrypted images. The encryption is carried out by using a random unitary transform. The proposed scheme offers two prominent features. 1) It is capable of
pattern recognition that works in the encrypted image domain. Even if data leaks, privacy can be maintained because data remains encrypted. 2) It realizes Encryption-then-Compression (EtC) systems, where image encryption is conducted prior to compression. The pattern recognition can be carried out using a
few sparse coefficients. On the basis of the pattern recognition results, the scheme can compress selected images with high quality by estimating a sufficient number of sparse coefficients. We use the INRIA dataset to demonstrate its performance in detecting humans in images. The proposal is shown to realize human detection with encrypted images and efficiently compress the images selected in the image recognition stage.
IMPROVING OF ARTIFICIAL NEURAL NETWORKS PERFORMANCE BY USING GPU’S: A SURVEYcsandit
This document provides a survey of improving the performance of artificial neural networks (ANNs) through parallel programming on GPUs. It discusses different ANN training strategies that can be parallelized, such as perceptrons, support vector machines, and spiking neural networks. GPUs provide significant speed advantages over CPUs for ANN training. The document reviews various studies that have implemented ANNs using GPUs and FPGAs, finding that GPUs reduce training time compared to CPUs, especially for algorithms involving large matrix operations like support vector machines. Spiking neural networks are better suited to FPGAs or custom circuits due to their complex temporal dynamics. The document concludes that GPUs are generally the best approach for ANN parallelization, but the
Improving of artifical neural networks performance by using gpu's a surveycsandit
In this paper we study the improvement in the performance of Artificial Neural Networks (ANN)
by using parallel programming in GPU or FPGA architectures. It is well known that ANN can
be parallelized according to particular characteristics of the training algorithm. We discuss
both approaches: the software (GPU) and the Hardware (FPGA). Different training strategies
are discussed: the Perceptron training unit, the Support Vector Machines (SVM) and Spiking
Neural Networks (SNN). The different approaches are evaluated by the training speed and
performance. On the other hand, algorithms were coded by authors in the hardware, like Nvidia
card, FPGA or sequential circuits that depends on methodology used, to compare learning time
with between GPU and CPU. Also, the main applications were made for recognition pattern,
like acoustic speech, odor and clustering According to literature, GPU has a great advantage
compared to CPU, this in the learning time except when it implies rendering of images, despite
several architectures of Nvidia cards and CPU’s. Also, in the survey we introduce a brief
description of the types of ANN and its techniques of execution to be related with results of
researching.
Design a New Image Encryption using Fuzzy Integral Permutation with Coupled C...IJORCS
This document proposes a new image encryption algorithm combining DNA sequence addition and coupled chaotic maps. The algorithm has two parts: 1) A DNA sequence matrix is obtained by encoding image pixels and divided into blocks that are added using Sugeno fuzzy integral, 2) The modified color components are encrypted using coupled two-dimensional piecewise nonlinear chaotic maps to strengthen security. Experimental results on image databases show the algorithm effectively protects digital image security over the internet.
Performance Evaluation of Object Tracking Technique Based on Position VectorsCSCJournals
This document presents a novel algorithm for object tracking in video frames based on position vectors. The algorithm first extracts position vectors for the object in the first frame. It then tracks the object across subsequent frames by cropping each new frame into blocks based on shifted position vectors and performing block matching between frames using feature vectors extracted by discrete wavelet transform (DWT) or dual tree complex wavelet transform (DTCWT). Experimental results on video sequences show the algorithm using DTCWT achieves higher tracking precision (95%) compared to DWT (92%). The algorithm is computationally efficient and can track multiple moving and still objects.
The code reads in a grayscale image, calculates its histogram using a specified number of bins, and plots the histogram. It also determines the maximum and minimum pixel values in the image and uses these to rescale the pixel values before calculating the histogram.
Robust Adaptive Threshold Algorithm based on Kernel Fuzzy Clustering on Image...cscpconf
The document presents a robust adaptive threshold algorithm based on kernel fuzzy clustering for image segmentation. It proposes using kernel fuzzy c-means clustering (KFCM) to generate adaptive thresholds for segmenting images. KFCM computes fuzzy membership values for pixels to cluster them. The algorithm was tested on MR brain images and showed good performance in detecting large and small objects while also enhancing low contrast images. Experimental results demonstrated the efficiency and accuracy of combining an adaptive threshold algorithm with KFCM for medical image segmentation.
Data Hiding Method With High Embedding Capacity CharacterCSCJournals
Recently, the data hiding method based on the high embedding capacity by using improved EMD method was proposed by Kuo et al.[6]. They claimed that their scheme can not only hide a great deal of secret data but also keep high safety and good image quality. However, in their scheme, the sender and the receiver must share the synchronous random secret seed before they transmit the stego-image each other. Otherwise, they can not recover the correct secret information from the stego-image. In this paper we propose an improved scheme based on EMD and LSB matching method to overcome the above problem, in other words, the sender does not share the synchronous random secret seed the receiver before the stego-image is transmitted. Observing the experimental results, they show that our proposed scheme acquires high embedding capacity and acceptable stego-image quality.
Performance boosting of discrete cosine transform using parallel programming ...IAEME Publication
This document summarizes a paper that proposes using parallel programming techniques to improve the performance of the discrete cosine transform (DCT) algorithm. It describes implementing both thread-level parallelism by distributing image blocks across multiple processor cores, and vector-level parallelism by performing SIMD operations within each core using AVX instructions. The proposed methodology uses Cilk Plus to enable parallelization at both the thread and vector levels. It is estimated that this multi-level parallel approach could theoretically provide a speedup of up to 32 times compared to a serial scalar implementation.
Black-box modeling of nonlinear system using evolutionary neural NARX modelIJECEIAES
Nonlinear systems with uncertainty and disturbance are very difficult to model using mathematic approach. Therefore, a black-box modeling approach without any prior knowledge is necessary. There are some modeling approaches have been used to develop a black box model such as fuzzy logic, neural network, and evolution algorithms. In this paper, an evolutionary neural network by combining a neural network and a modified differential evolution algorithm is applied to model a nonlinear system. The feasibility and effectiveness of the proposed modeling are tested on a piezoelectric actuator SISO system and an experimental quadruple tank MIMO system.
TRANSFER LEARNING BASED IMAGE VISUALIZATION USING CNNijaia
Image classification is a popular machine learning based applications of deep learning. Deep learning techniques are very popular because they can be effectively used in performing operations on image data in large-scale. In this paper CNN model was designed to better classify images. We make use of feature extraction part of inception v3 model for feature vector calculation and retrained the classification layer with these feature vector. By using the transfer learning mechanism the classification layer of the CNN model was trained with 20 classes of Caltech101 image dataset and 17 classes of Oxford 17 flower image dataset. After training, network was evaluated with testing dataset images from Oxford 17 flower dataset and Caltech101 image dataset. The mean testing precision of the neural network architecture with Caltech101 dataset was 98 % and with Oxford 17 Flower image dataset was 92.27 %.
Human Action Recognition using Contour History Images and Neural Networks Cla...IRJET Journal
This document proposes a new method for human action recognition using contour history images extracted from silhouettes, tracking of the body's center movement, and the relative dimensions of the bounding box containing each contour history image. Features are extracted and reduced using three different methods: dividing the contour history images into rectangles, a shallow autoencoder neural network, and a deep autoencoder neural network. The reduced features are classified using a neural network classifier. The proposed method achieved a recognition rate of 98.9% on a standard human action dataset, demonstrating its potential for real-time human action recognition applications.
Real-time Multi-object Face Recognition Using Content Based Image Retrieval (...IJECEIAES
Face recognition system in real time is divided into three processes, namely feature extraction, clustering, detection, and recognition. Each of these stages uses different methods, Local Binary Pattern (LBP), Agglomerative Hierarchical Clustering (AHC) and Euclidean Distance. Multi-face image search using Content Based Image Retrieval (CBIR) method. CBIR performs image search by image feature itself. Based on real time trial results, the accuracy value obtained is 61.64%.
GSM technology is used to monitor the different parameters of an ICU patient remotely and also control over medicine dosage is provided. Measurements of vital signs and behavioral patterns can be translated into accurate predictors of health risk ,even at an early stage and can be combined with alarm triggering systems in order to initiate the appropriate actions. The conventional methods including wet adhesive Ag/AgCl electrodes for HR and HRV, the capnograph device for respiratory status and pulse oximetry for oxyhemoglobin saturation provide excellent signals but are expensive, troublesome and inconvenient. A method to monitor physiological information based on GSM offers a new means for health monitoring. In this paper, we review the latest developments in monitoring and discuss the challenges and future directions for this field.
Supercapacitors or EDLCs (i.e. electric double-layer capacitors) or ultra-capacitors are becoming increasingly popular as alternatives for the conventional and traditional battery sources. This brief overview focuses on the different types of supercapacitors, the relevant quantitative modeling areas and the future of supercapacitor research and development. Supercapacitors may emerge as the solution for many application-specific power systems. Especially, there has been great interest in developing supercapacitors for electric vehicle hybrid power systems, pulse power applications, as well as back-up and emergency power supplies. Because of their flexibility, however, supercapacitors can be adapted to serve in roles for which electrochemical batteries are not as well suited. Also, supercapacitors have some intrinsic characteristics that make them ideally suited to specialized roles and applications that complement the strengths of batteries. In particular, supercapacitors have great potential for applications that require a combination of high power, short charging time, high cycling stability and long shelf life. So, let’s just begin the innovative journey of these near future of life-long batteries that can charge up almost anything and everything within a few seconds!
In this study, trans-consonantal vowel-to-vowel anticipatory coarticulation in Chinese is investigated. The target words are in the form of 'ba.bV2', and the subjects are eight native speakers of standard Chinese. Vowel formants are examined at the offset, middle and onset points of the target vowel. Results show that trans-segmental coarticulation exists in Chinese, especially at the offset point of the target vowel. Coarticulation is more likely to occur on F2, and in Chinese, coarticulatory effect does not extend to the onset point of the vowel.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
High dimensional data presents a challenge for the clas-sification problem because of the diffculty in modeling the precise relationship between the large number of the class variable and feature variables. In such cases, it can be desirable to reduce the information for a small number of dimensions in order to improve the accuracy and effectiveness of the classification process. While data reduction has been a well studied problem for the unsupervised domain, this technique has not been explored as extensively for the supervised case. for practical use in the high dimensional case the existing techniques which try to perform dimensional- ity reduction are too slow. These techniques find global discriminants in the data. However, the data behavior often varies with data locality and different subspaces may show better discrimination in different localities. This is the more challenging task than the global discrimination problem because of the data localization issue. In this paper, I propose the PCA(Principal Component Analysis) method in order to create a reduced representation of the data for classification applications in an efficient and effective way. Because of this method, the procedure is extremely fast and scales almost linearly both with data set size and dimensionality.
The steady laminar two dimensional stagnation point flow of an incompressible electrically conducting magneto-micropolar fluid over a permeable stretching surface with heat source/sink and viscous dissipation in the presence of mass transfer and chemical reaction has been studied. Using the similarity transformations, the governing equations have been transformed into a system of ordinary differential equations. These differential equations are highly nonlinear which cannot be solved analytically. Therefore, forth order Runge-Kutta method along with shooting technique has been used for solving it. Numerical results are obtained for the skin-friction coefficient, the local Nusselt number and Sherwood number as well as the velocity, temperature and concentration profiles for different values of the governing parameters, namely, velocity ratio parameter, boundary parameter, material parameter, magnetic parameter, Prandtl number, Eckert number, heat source/sink parameter, Schmidt number and chemical reaction parameter.
The effect of wind speed on a 5 × 5 fan air cooled steam condenser (ACC) under windy conditions is investigated using computational fluid dynamics. It is found that cross winds significantly reduce the air flow rate that is delivered by the fans in normal conditions. The effect of wind speed is found to be varying for different fan deck heights of the air cooled condenser. It is recommended that at the initial stage of a power plant which is equipped with an air cooled condenser, the wind effects analysis is necessary and helpful in mitigating the adverse effect of winds.
Vehicle routing problem is a NP-hard problem, with the expansion of problem solving more difficult.
This paper proposes a hybrid behavior based on ant colony algorithm to solve the problem, ant to different
objectives in the first place as the path selection according to the analysis of the impact on the algorithm, then
define the ant behavior and design four concrete ant behavior by selecting different ways of ant behavior to
form different improved algorithm. Finally, experimental results show that the improved algorithm can solve
vehicle routing problems quickly and effectively.
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.
An Advance Approach of Image Encryption using AES, Genetic Algorithm and RSA ...IJEACS
In current scenario the entire world is moving towards digital communication for fast and better communication. But in this a problem rises with security i.e. when we have to store information (either data or image) at any casual location or transmit information through internet. As internet is an open transmission medium, security of data becomes very important. To defend our information from piracy or from hacking we use a technique and i.e. known as Encryption Technique. In this paper, we use image as information and use an advance approach of well-known encryption techniques like AES, Genetic Algorithm, and RSA algorithm to encrypt it and keep our information safe from hackers or intruders making it highly difficult and time consuming to decipher the image without using the key.
Image Encryption Using Advanced Hill Cipher AlgorithmIDES Editor
The Hill cipher algorithm is one of the symmetric
key algorithms that have several advantages in data
encryption. But, the inverse of the key matrix used for
encrypting the plaintext does not always exist. Then if the
key matrix is not invertible, then encrypted text cannot be
decrypted. In the Involutory matrix generation method the
key matrix used for the encryption is itself invertible. So, at
the time of decryption we need not to find the inverse of the
key matrix. The objective of this paper is to encrypt an
image using a technique different from the conventional Hill
Cipher. In this paper a novel advanced Hill (AdvHill)
encryption technique has been proposed which uses an
involutory key matrix. The scheme is a fast encryption
scheme which overcomes problems of encrypting the images
with homogeneous background. A comparative study of the
proposed encryption scheme and the existing scheme is
made. The output encrypted images reveal that the
proposed technique is quite reliable and robust.
The document proposes and evaluates a new digital image security scheme that uses Residue Number System (RNS) encoding/decoding and a modified Arnold transform algorithm. Key points:
- The encryption process encodes the plain image into residual images using RNS, then encrypts them by applying the modified Arnold transform multiple times.
- The decryption process decrypts the cipher image by applying the inverse Arnold transform, then decodes the residual images back into the plain image using RNS and the Chinese Remainder Theorem.
- Experimental results on images of different sizes show the scheme can encrypt/decrypt without information loss. Security analysis indicates resistance to statistical attacks like histograms and strong sensitivity to encryption keys.
The document proposes and evaluates a new digital image security scheme that uses Residue Number System (RNS) encoding/decoding and a modified Arnold transform algorithm. Key points:
- The encryption process encodes the plain image into residual images using RNS, then encrypts them using the modified Arnold transform.
- The decryption process decrypts the cipher image using the inverse Arnold transform, then decodes the residual images back into the plain image using RNS and the Chinese Remainder Theorem.
- Experimental results on test images of different sizes and formats show the scheme can effectively encrypt and decrypt without information loss. Security analysis also indicates resistance to statistical attacks like histograms and strong sensitivity to encryption keys.
Robust Watermarking Technique using 2D Logistic Map and Elliptic Curve Crypto...idescitation
Copyright protection is a vital issue in modern day’s data transmission over
internet. For copyright protection, watermarking technique is extensively used. In this
paper, we have proposed a robust watermarking scheme using 2D Logistic map and elliptic
curve cryptosystem (ECC) in the DWT domain. The combined encryption has been taken to
enhance the security of the watermark before the embedding phase. The PSNR value shows
the difference between original cover and embedded cover is minimal. Similarly, NC values
show the robustness and resistance capability of the proposed technique from the common
attacks such as scaling, Gaussian noise etc. Thus, this combined version of 2D Logistic map
and Elliptic curve cryptosystem can be used in case of higher security requirement of the
watermark signal.
Image encryption using chaotic sequence and its cryptanalysisIOSR Journals
1) The document analyzes an image encryption algorithm that uses chaotic sequences. It finds that the algorithm can be broken with only a small number of known or chosen plaintexts using two attacks.
2) A chosen plaintext attack is described that requires only one known plaintext and two chosen plaintexts to reveal the secret chaotic sequences and encryption keys.
3) A known plaintext attack is also introduced that requires two known plaintext-ciphertext pairs to determine the secret parameters and completely break the encryption scheme.
COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMSIJNSA Journal
This paper proposed a novel color image encryption scheme based on multiple chaotic systems. The ergodicity property of chaotic system is utilized to perform the permutation process; a substitution
operation is applied to achieve the diffusion effect. In permutation stage, the 3D color plain-image matrix
is converted to a 2D image matrix, then two generalized Arnold maps are employed to generate hybrid chaotic sequences which are dependent on the plain-image’s content. The generated chaotic sequences are then applied to perform the permutation process. The encryption’s key streams not only depend on the
cipher keys but also depend on plain-image and therefore can resist chosen-plaintext attack as well as
known-plaintext attack. In the diffusion stage, four pseudo-random gray value sequences are generated by another generalized Arnold map. The gray value sequences are applied to perform the diffusion process by bitxoring operation with the permuted image row-by-row or column-by-column to improve the encryption rate. The security and performance analysis have been performed, including key space analysis, histogram analysis, correlation analysis, information entropy analysis, key sensitivity analysis, differential analysis etc. The experimental results show that the proposed image encryption scheme is highly secure thanks to its large key space and efficient permutation-substitution operation, and therefore it is suitable for practical image and video encryption.
COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMSIJNSA Journal
This paper proposed a novel color image encryption scheme based on multiple chaotic systems. The ergodicity property of chaotic system is utilized to perform the permutation process; a substitution operation is applied to achieve the diffusion effect. In permutation stage, the 3D color plain-image matrix is converted to a 2D image matrix, then two generalized Arnold maps are employed to generate hybrid chaotic sequences which are dependent on the plain-image’s content. The generated chaotic sequences are then applied to perform the permutation process. The encryption’s key streams not only depend on the cipher keys but also depend on plain-image and therefore can resist chosen-plaintext attack as well as
known-plaintext attack. In the diffusion stage, four pseudo-random gray value sequences are generated by
another generalized Arnold map. The gray value sequences are applied to perform the diffusion process by bitxoring operation with the permuted image row-by-row or column-by-column to improve the encryption rate. The security and performance analysis have been performed, including key space analysis, histogram analysis, correlation analysis, information entropy analysis, key sensitivity analysis, differential analysis
etc. The experimental results show that the proposed image encryption scheme is highly secure thanks to its
large key space and efficient permutation-substitution operation, and therefore it is suitable for practical image and video encryption.
COLOR IMAGE ENCRYPTION BASED ON MULTIPLE CHAOTIC SYSTEMSIJNSA Journal
This document proposes a novel color image encryption scheme based on multiple chaotic systems. The scheme utilizes the ergodic properties of chaotic systems to perform pixel permutation and applies a substitution operation to achieve diffusion. In the permutation stage, two generalized Arnold maps are used to generate hybrid chaotic sequences to permute pixel positions. In the diffusion stage, four pseudo-random gray value sequences generated by another generalized Arnold map are used to diffuse the permuted image via bitwise XOR operations. Security analysis shows the scheme has a large key space and is highly secure against statistical attacks, differential attacks, and chosen/known plaintext attacks.
Design a cryptosystem using elliptic curves cryptography and Vigenère symmetr...IJECEIAES
In this paper describes the basic idea of elliptic curve cryptography (ECC) as well as Vigenère symmetry key. Elliptic curve arithmetic can be used to develop elliptic curve coding schemes, including key exchange, encryption, and digital signature. The main attraction of elliptic curve cryptography compared to Rivest, Shamir, Adleman (RSA) is that it provides equivalent security for a smaller key size, which reduces processing costs. From the theorical basic, we proposed a cryptosystem using elliptic curves and Vigenère cryptography. We proposed and implemented our encryption algorithm in an integrated development environment named visual studio 2019 to design a safe, secure, and effective cryptosystem.
Comparative Performance of Image Scrambling in Transform Domain using Sinusoi...CSCJournals
With the rapid development of technology, and the popularization of internet, communication is been greatly promoted. The communication is not limited only to information but also includes multimedia information like digital Images. Therefore, the security of digital images has become a very important and practical issue, and appropriate security technology is used for those digital images containing confidential or private information especially. In this paper a novel approach of Image scrambling has been proposed which includes both spatial as well as Transform domain. Experimental results prove that correlation obtained in scrambled images is much lesser then the one obtained in transformed images.
Encryption-Decryption RGB Color Image Using Matrix Multiplicationijcsit
An enhanced technique of color image encryption based on random matrix key encoding is proposed. To
encrypt the color image a separation into Red Green and Blue (R, G, B) channels will applied. Each
channel is encrypted using a technique called double random matrix key encoding then three new coding
image matrices are constructed. To obtain the reconstructed image that is the same as the original image
in the receipted side; simple extracted and decryption operations can be maintained. The results shown
that the proposed technique is powerful for color image encryption and decryption and a MATLAB and
simulations were used to get the results.
The proposed technique has high security features because each color component is separately treated
using its own double random matrix key which is generated randomly and make the process of hacking the
three keys very difficult.
This document describes an image encryption and decryption technique using chaos algorithms. It uses the chaotic properties of the Henon map and Arnold cat map. The Henon map is used to generate pseudo-random key values for pixel shuffling. Pixel positions of the input image are first shuffled using the Arnold cat map. Then they are shuffled again using the sorted key values from the Henon map. This encrypts the image. Decryption reverses the process to recover the original pixel values and image. Experimental results show the encrypted image is secure and the original image can be recovered accurately using the correct key during decryption. The technique provides efficient and secure encryption of images for transmission.
DESIGN AND ANALYSIS OF A NOVEL DIGITAL IMAGE ENCRYPTION SCHEMEIJNSA Journal
In this paper, a new image encryption scheme using a secret key of 144-bits is proposed. In the substitution process of the scheme, image is divided into blocks and subsequently into color components. Each color component is modified by performing bitwise operation which depends on secret key as well as a few most significant bits of its previous and next color component. Three rounds are taken to complete substitution process. To make cipher more robust, a feedback mechanism is also applied by modifying used secret key after encrypting each block. Further, resultant image is partitioned into several key based dynamic sub-images. Each sub-image passes through the scrambling process where pixels of sub-image are reshuffled within itself by using a generated magic square matrix. Five rounds are taken for scrambling process. The propose scheme is simple, fast and sensitive to the secret key. Due to high order of substitution and permutation, common attacks like linear and differential cryptanalysis are infeasible. The experimental results show that the proposed encryption technique is efficient and has high security features.
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.
This document provides an overview of elliptic curve cryptography (ECC). It discusses how ECC provides stronger security than RSA with smaller key sizes. The document describes the mathematical foundations of elliptic curves over finite fields. It explains scalar multiplication, which involves adding a point on the elliptic curve to itself multiple times, as the core operation in ECC. Finally, it discusses implementations of ECC and applications for encryption and digital signatures.
IRJET- An Image Cryptography using Henon Map and Arnold Cat MapIRJET Journal
The document proposes a new symmetric image encryption algorithm based on the Henon chaotic system and Arnold Cat map. The algorithm uses Henon map to generate pseudo-random key values for pixel encryption and Arnold Cat map for pixel shuffling. Encryption involves XORing pixel values with keys and shuffling pixels, while decryption reverses these processes to recover the original image using the same keys.
Image encryption using elliptical curve cryptosytem with hill cipherkarthik kedarisetti
IMAGE ENCRYPTION-BTECH FINAL YEAR PROJECT ZEROTH REVIEW.
Image encryption is rapidly increased recently by the increasing use of the internet and communication
media. Sharing important images over unsecured channels is liable for attacking and stealing. Encryption
techniques are the suitable methods to protect images from attacks. Hill cipher algorithm is one of the
symmetric techniques, it has a simple structure and fast computations, but weak security because sender
and receiver need to use and share the same private key within a non-secure channels. A new image
encryption technique that combines Elliptic Curve Cryptosystem with Hill Cipher (ECCHC) has been proposed
in this paper to convert Hill cipher from symmetric technique to asymmetric one and increase its
security and efficiency and resist the hackers. Self-invertible key matrix is used to generate encryption
and decryption secret key. So, no need to find the inverse key matrix in the decryption process. A secret
key matrix with dimensions 4 4 will be used as an example in this study. Entropy, Peak Signal to Noise
Ratio (PSNR), and Unified Average Changing Intensity (UACI) will be used to assess the grayscale image
encryption efficiency and compare the encrypted image with the original image to evaluate the performance
of the proposed encryption technique.
Information security is one of the most important issues in the
recent times. Elliptic Curve Cryptography (ECC) is one of the most
efficient public key cryptosystems that is secured against adversaries
because it is hard for them to find the secret key and solve
the elliptic curve discrete logarithm problem. Its strengthened
security also comes from the small key size that is used in it with
the same level of safety compared to the other cryptosystems like RSA(Rivest–Shamir–Adleman))
A New Security Level for Elliptic Curve Cryptosystem Using Cellular Automata ...Editor IJCATR
Elliptic curve cryptography (ECC) is an effective approach to protect privacy and security of information. Encryption
provides only one level of security during transmission over the channel. Hence there is a need for a stronger encryption which is very
hard to break. So, to achieve better results and improve security, information has to pass through several levels of encryption. The aim
of this paper would be to provide two levels of security. First level comprises of plaintext using as security key compressed block to
encrypt text based ECC technique and the second level comprises of scrambling method with compression using 2D Cellular rules. In
particular, we propose an efficient encryption algorithm based ECC using Cellular automata and it is termed as Elliptic Curve
Cryptosystem based Cellular Automata (ECCCA). This paper presents the implementation of ECCCA for communication over
insecure channel. The results are provided to show the encryption performance of the proposed method.
Similar to Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve (20)
This document discusses the impact of data mining on business intelligence. It begins by defining business intelligence as using new technologies to quickly respond to changes in the business environment. Data mining is an important part of the business intelligence lifecycle, which includes determining requirements, collecting and analyzing data, generating reports, and measuring performance. Data mining allows businesses to access real-time, accurate data from multiple sources to improve decision making. Using business intelligence and data mining techniques can help businesses become more efficient and make better decisions to increase profits and customer satisfaction. The expected results of applying business intelligence include improved decision making through accurate, timely information to support organizational goals and strategic plans.
This document presents a novel technique for solving the transcendental equations of selective harmonics elimination pulse width modulation (SHEPWM) inverters based on the secant method. The proposed algorithm uses the secant method to simplify the numerical solution of the nonlinear equations and solve them faster compared to other methods. Simulation results validate that the proposed method accurately estimates the switching angles to eliminate specific harmonics from the output voltage waveform and achieves near sinusoidal output current for various modulation indices and numbers of harmonics eliminated.
This document summarizes a research paper that designed and implemented a dual tone multi-frequency (DTMF) based GSM-controlled car security system. The system uses a DTMF decoder and GSM module to allow a car to be remotely controlled and secured from a mobile phone. It works by sending DTMF tones from the phone through calls to the GSM module in the car. The decoder interprets the tones and a microcontroller executes commands to disable the ignition or control other devices. The system was created to improve car security and accessibility through remote monitoring and control with DTMF and GSM technology.
This document presents an algorithm for imperceptibly embedding a DNA-encoded watermark into a color image for authentication purposes. It applies a multi-resolution discrete wavelet transform to decompose the image. The watermark, encoded into DNA nucleotides, is then embedded into the third-level wavelet coefficients through a quantization process. Specifically, the watermark nucleotides are complemented and used to quantize coefficients in the middle frequency band, modifying the coefficients. The watermarked image is reconstructed through inverse wavelet transform. Extraction reverses these steps to recover the watermark without the original image. The algorithm aims to balance imperceptibility and robustness through this wavelet-based, blind watermarking scheme.
1) The document analyzes the dynamic saturation point of a deep-water channel in Shanghai port based on actual traffic data and a ship domain model.
2) A dynamic channel transit capacity model is established that considers factors like channel width, ship density, speed, and reductions due to traffic conditions.
3) Based on AIS data from the channel, the average traffic flow is calculated to be 15.7 ships per hour, resulting in a dynamic saturation of 32.5%, or 43.3% accounting for uneven day/night traffic volumes.
The document summarizes research on the use of earth air tunnels and wind towers as passive solar techniques. Key findings include:
- Earth air tunnels circulate air through underground pipes to take advantage of the stable temperature 4 meters below ground for cooling in summer and heating in winter. Testing showed the technique can reduce ambient temperatures by up to 14 degrees Celsius.
- Wind towers circulate air through tall shafts to cool air entering buildings at night and provide downward airflow of cooled air during the day.
- Experimental testing of an earth air tunnel system over multiple months found maximum temperature reductions of 33% in spring and minimum reductions of 15% in summer.
The document compares the mechanical and physical properties of low density polyethylene (LDPE) thin films and sheets reinforced with graphene nanoparticles. LDPE/graphene thin films were produced via solution casting, while sheets were made by compression molding. Testing showed that the thin films had enhanced tensile strength, lower melt flow index, and higher thermal stability compared to sheets. The tensile strength of thin films increased by up to 160% with 1% graphene, while sheets increased by 70%. Melt flow index decreased more for thin films, indicating higher viscosity. Thin films also showed greater improvement in glass transition temperature. These results demonstrate that processing technique affects the properties of LDPE/graphene nanocomposites.
The document describes improvements made to a friction testing machine. A stepper motor and PLC control system were added to automatically vary the load on friction pairs, replacing the manual method. Tests using the improved machine found that the friction coefficient decreases as the load increases, and that abrasive and adhesive wear increased with higher loads. The improved machine allows more accurate and convenient testing of friction pairs under varying load conditions.
This document summarizes a research article that investigates the steady, two-dimensional Falkner-Skan boundary layer flow over a stationary wedge with momentum and thermal slip boundary conditions. The flow considers a temperature-dependent thermal conductivity in the presence of a porous medium and viscous dissipation. Governing partial differential equations are non-dimensionalized and transformed into ordinary differential equations using similarity transformations. The equations are highly nonlinear and cannot be solved analytically, so a numerical solver is used. Numerical results are presented for the skin friction coefficient, local Nusselt number, velocity and temperature profiles for varying parameters like the Falkner-Skan parameter and Eckert number.
An improvised white board compass was designed and developed to enhance the teaching of geometrical construction concepts in basic technology courses. The compass allows teachers to visually demonstrate geometric concepts and constructions on a white board in an engaging, hands-on manner. It supports constructivist learning principles by enabling students to observe and emulate the teacher. The design process utilized design and development research methodology to test educational theories and validate the practical application of the compass. The improvised compass was found to effectively engage students and improve their performance in learning geometric constructions.
The document describes the design of an energy meter that calculates energy using a one second logic for improved accuracy. The meter samples voltage and current values using an ADC synchronized to the line frequency via PLL. It calculates active and reactive power by averaging the sampled values over each second. The accumulated active power for each second is multiplied by one second to calculate energy, which is accumulated and converted to kWh. Test results showed the meter achieved an error of 0.3%, within the acceptable limit for class 1 meters. Considering energy over longer durations like one second helps reduce percentage error in the calculation.
This document presents a two-stage method for solving fuzzy transportation problems where the costs, supplies, and demands are represented by symmetric trapezoidal fuzzy numbers. In the first stage, the problem is solved to satisfy minimum demand requirements. Remaining supplies are then distributed in the second stage to further minimize costs. A numerical example demonstrates using robust ranking techniques to convert the fuzzy problem into a crisp one, which is then solved using a zero suffix method. The total optimal costs from both stages provide the solution to the original fuzzy transportation problem.
1) The document proposes using an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller for a Distributed Power Flow Controller (DPFC) to improve voltage regulation and power quality in a transmission system.
2) A DPFC is placed at a load bus in an IEEE 4 bus system and its performance is compared using a PI controller and ANFIS controller.
3) Simulation results show the ANFIS controller provides faster convergence and better voltage profile maintenance during voltage sags and swells compared to the PI controller.
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Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve
1. International Journal of Engineering Inventions
e-ISSN: 2278-7461, p-ISSN: 2319-6491
Volume 3, Issue 11 (June 2014) PP: 8-16
www.ijeijournal.com Page | 8
Security Enhancement of Image Encryption Based on
Matrix Approach using Elliptic Curve
F. Amounas1
and E.H. El Kinani2
,
1, 2
(R.O.I Group, Computer Sciences Department, A.A Group, Mathematical Department, Moulay Ismaïl
University, Faculty of Sciences and Technics, Errachidia, Morocco)
Abstract: Encryption is used to securely transmit data in open networks. Each type of data has its own
features. With the rapid growth of internet, security of digital images has become more and more important.
Therefore different techniques should be used to protect confidential image data from unauthorized access. In
this paper an encryption technique based on elliptic curves for securing images to transmit over public channels
will be proposed. Encryption and decryption process are given in details with an example. The comparative
study of the proposed scheme and the existing scheme is made. Our proposed algorithm is aimed at better
encryption of all types of images even ones with uniform background and makes the image encryption scheme
more secure. The output encrypted images reveal that the proposed method is robust.
Keywords: Image Encryption, Elliptic Curve Cryptography, Involutory Matrix, Elliptic Curve Discrete
Logarithm Problem, Mapping technique.
I. INTRODUCTION
With the huge growth of computer networks and the latest advances in digital technologies, a huge
amount of digital data is being exchanged over various networks. And therefore, with rapid evolution of
internet, confidentiality of digital images has become prime concern.
Multimedia data including video, audio, images, etc form large files, thus making their transmission
difficult. But, with rapid growth of internet large multimedia files are easily transmitted over networks.
Research work on image encryption methods has become prime concern and has attracted attention recently.
But, the problem identified in this route is, that most of the available encryption algorithms are used for text
data. Though, the multimedia storage and transmission also needs to be protected against unauthorised
duplication and consumption, and, unauthorized disclosure and misuse. There by, posing a need of good
encryption technique ensuring users privacy and copyright ownership. Many different image encryption
methods have been proposed to enhance digital image security. Image encryption techniques try to convert an
image to another one that is hard to understand. On the other hand, image decryption retrieves the original
image from the encrypted one.
In the literature, there are two major groups of image encryption algorithms: (a) non-chaos selective
methods and (b) chaos-based selective or non-selective methods. Most of these algorithms are designed for a
specific image format compressed or uncompressed, and some of them are even format compliant. In [1], the
authors have studied the encryption and decryption of the text with simple example and the work is extended to
the image applications. In [2], Megha Kolhekar and al. have studied application of elliptic curves over finite
fields for traditional key exchange and encryption of text. It has implemented the proposed scheme for
encryption of images. In [3], G. Zhu et al. have tried to encrypt an image by scrambling pixels and then adding a
watermark to scrambled image. Then, they encrypted scrambling parameters using ECC. In our previous works
[4], [5] and [6], we have proposed cryptographic algorithm for text encryption using elliptic curve. We also
described how to combine steganography with cryptography using Amazigh alphabet [7].
The main motivation of this work is to propose a novel encryption algorithm to encrypt an image based
elliptic curve. The most important phase in encryption based ECC is transformation algorithm using mapping
technique. The paper is organized as follows: the basic concept of elliptic curve is outlined in section 2. Section
3 discusses about the involutory matrix. In section 4, the proposed method is explained in detail. Section 5
presents the implementation with an example. Experimental results are discussed in section 6. Finally, section 7
describes the concluding remarks.
II. MATHEMATICAL BACKGROUND OF ELLIPTIC CURVE
The elliptic curves are not the same as an ellipse. They are named so because they are described by
cubic equations. An elliptic curve may be defined as a set of points on the coordinate planes, satisfying the
equation of the form,
2. Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve
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E: y2
= x3
+ ax + b mod p, (1)
(where p 2, 3 is a prime number).
2.1. Curve Operations
The crucial property of an elliptic curve is that, the resultant point obtained by adding two points on the
curve is also on the curve. The addition rule satisfies the normal properties of addition. If P1 = (x1, y1) and P2 =
(x2, y2) are points on the elliptic curve, the addition rule has the form:
(x1, y1) + (x2, y2) = (x3, y3) (2)
where
x3 = t2
- x1 - x2 mod (p) (3)
y3 = t(x1 - x3) - y1 mod (p) (4)
with
12
12
xx
yy
if P1 P2
t=
1
2
1
2
3
y
ax
if P1 = P2
It is know that rational points form an additive group in the addition over the elliptic curve shown in the
following figure:
Figure 1. Addition of points on elliptic curve
Multiplication P over an elliptic group is computed by repeating the addition operation times by (3)
and (4). The strength of an ECC cryptosystem is depends on difficulty of finding the number of times that P is
added to itself to get P. Reverse operation known as Elliptic Curve Discrete Logarithm Problem (ECDLP).
2.2. Discrete Logarithm Problem on Elliptic Curve (ECDLP)
ECC is based on the discrete logarithm problem applied to elliptic curves over a finite field [8]. More
precisely, for an elliptic curve E, it relies on the fact that it is easy to compute Q = P, for in Fp and P, Q in E.
However there is currently no known sub exponential algorithm to compute given P and Q. In fact the discrete
logarithm problem can be used to build cryptosystems with finite Abelian group. Indeed multiplicative groups in
a finite field were originally proposed. In fact, the difficulty of the problem depends on the group, and at
present, the problem in elliptic curve groups is orders of magnitude harder than the same problem in a
multiplicative group of a finite field. This feature is a main strength of elliptic curve cryptosystems.
III. INVOLUTORY KEY MATRIX
In the literature, the various proposed methods can be found, some of them in [9, 10]. One of the
methods is explained below. A is called involutory matrix if A = A-1
. In our case, we generate the involutory key
matrix with elements are integers values that are the residus of modulo arithmetic of a number. This algorithm
can generate involutory matrices of order (nn) where n is even. Let A be an (nn) involutory matrix partitioned
to four sub-matrix noted A11, A12, A21 and A22.
3. Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve
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a1,1 a1,2 … a1,n
a2,1 a2,2 … a2,n
A = ...
an,1 an,2 … an,n
where Aij is a matrix of (
2
n
2
n
) order.
So that, A12A21 = I - 2
11A = (I - A11)(I + A11).
If A12 is one of the factors of (I- 2
11A ), then A21 is the other. Solving the second matrix equation results A11+A22 = 0, then
form the matrix.
The algorithm is given below:
1. Select any arbitrary matrix A22 of (
2
n
2
n
) order.
2. Obtain A11 = -A22.
3. Take A12 = (I - A11) or (I + A11) where is a non-vanishing number (0).
4. Then A21 =
1
(I + A11) or
1
(I - A11).
5. Form the matrix completely.
The proposed method uses an involutory key matrix for encryption process.
IV. MAIN RESULTS
4.1. Proposed Method
The common feature of our previous works [11, 12], is the use of ECC mechanism for text encryption
based matrix approach. Here, we extend this approach to encrypt image using transformation Algorithm.
Every image consists of pixels. In gray scale images each pixel has an 8-bit value between 0 and 255. In color
images each pixel defined by three 8-bit values separately demonstrate the Red, Green and Blue intensity. To
encrypt an image using ECC, each pixel is considered as a point on elliptic curve.
4.1.1. Transformation Algorithm
In this paper, proposed mapping technique is based on transformation process that works as follows:
To define the map matrix, the elliptic group Ep (a, b) which is all possible points on the finite field are generated
first and then the original image is divided into data matrices of 88. The row indexes are start from 0 and end
with 63 for the first matrix, from 64 to 127 for the second, … Each row stands for a pixel intensity value.
Starting from the first pixel in plain image, the corresponded point with the intensity value in the matrix is
mapped to this pixel and continue to the last pixel. For any matrix, 64 points are selected in such directory by
following spiral technique with the first point is a secure key generated.
The generated (or transformed) image is then fed to the encryption algorithm. The main idea is that an image
can be viewed as an arrangement of matrices with its elements are points on elliptic curve.
Figure 2. Example of spiral matrix (4 4).
4. Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve
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The overview model of the proposed method using elliptic curve based Transformation Algorithm is shown in
Figure 3.
Figure 3.An overview diagram of the proposed method.
4.1.2. Encryption Algorithm
The output of the transformation process is served as input to the encryption algorithm. Image
encryption procedure is discussed below.
Suppose that we have some elliptic curve E defined over a finite field Fp and a point P on E (Fp) that P has prime
order N. The curve E and P are publicly known, as is the embedding system m Pm which imbed intensity
values on an elliptic curve E. Bob chooses a random integer nB, and publishes the point PB = nBP (while nB
remains secret).
Then when Alice wishes to encrypt an image and send it to Bob, she proceeds thus:
Step 1. Chooses a random integer k with 1 k N and compute R = kPB.
Step 2. Imbed the original image into points on elliptic curve using the transformation algorithm.
Then, the plain image is divided into data matrices of n n, noted Mi, i = 1, 2, …
P1,1 P1,2 … P1,n
P2,1 P2,2 … P2,n
Mi = …
Pn,1 Pn,2 … Pn,n
where Pm is the mapping point of intensity value m.
Step 3. A involutory matrix A of n n is constructed.
Step 4. Perform the product: Ci = MiA, (i=1, 2, … ) using addition and doubling points on elliptic curve.
Now, continue the same process until all pixels are crypted. The result can be represented as an
image.
Step 5. The cipher text is represented by (kP, Ci) where the second part is the encrypted image.
Therefore, the cipher text is transmitted to Bob through an insecure channel.
To decrypt the received image, Bob does the following:
Step 1. Extract the first block from the received cipher text. It is mapped to find its equivalent point noted
P1 = kP. Then, applies his secret key and Compute R = nBP1.
Step 2. Extract the remaining blocks and stored into square matrices of (n n).
Step 3. Generate the involutory matrix and compute Mi.
To view the encrypted points as an image, we refer to the data matrix (section 4.1.1) and find the current index
according to each point.
5. Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve
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V. ILLUSTRATION AND RESULTS
In this section, we consider the elliptic curve E73 (70, 57) given by the Weierstrass equation:
E: y2
mod 73 = x3
+ 70x + 57 mod 73 (5)
The elliptic curve contains 74 points. The base point P is selected as (3, 41).
To create the data matrix, the secure key will place in the row 0 which is corresponded to pixel with intensity
value of 0, and then continue next point with next value. After placing first 64 points in first matrix, next we
choose another point in the first row 0, then 64 points will place in second matrix and hereafter will do the same
for next points to the last. In this example, there are 74 points on the curve. These points completely fill 64
cellule of each matrix.
Hence we shall assume that nB = 13, k = 29, PB = (19; 56), R = (41, 69), for instance,
The data matrices generated is shown in Table 1.
(41, 69) (53, 72) … (19,56) (63, 67) (44, 31) (22, 28) … (58, 31) (41, 69)
(11, 48) (13, 5) … (4, 67) (12, 17) (23, 16) (1, 36) … (6, 6) (53, 72)
… … … … … … … … … …
(52, 38) (26, 20) … (19, 17) (35, 7) (12, 17) (22, 45) … (58, 42) (19,56)
(42, 17) (64, 42) … (47, 15) (60, 69) (4, 67) (50, 2) … (11, 48) (63, 67)
(63, 67) (11, 48) … (50,2) (4, 67) (6, 67) (12, 17) … (23,16) (44, 65)
(19, 56) (58, 42) … (22, 45) (12, 17) (50, 2) (22, 45) … (1, 36) (22, 28)
… … … … … … … … … …
(53, 72) (6, 6) … (1, 36) (23, 16) (11, 48) (58, 42) … (6, 6) (58, 31)
(41, 69) (58, 31) … (22, 28) (44, 65) (63, 67) (19, 56) … (53, 72) (41, 69)
Table 1. Data Grid generated.
To encrypt an image using this method, all pixels are mapped into points on elliptic curve using data
Grid generated (Table 1). The Table 2 demonstrate some pixels intensity value of the image chosen (“Lena”),
the result of mapping transformation of pixel to point on elliptic curve and the corresponding encrypted points.
After encrypting all the points using involutory matrix, in order to show the encrypted points as an image, first
create a matrix the same size of image, find each point in the data grid and then place the rang index in
equivalent element of created matrix.
To view the encrypted points as an image, we refer to the mapping data grid and find the current Number
according to each point and replace with the related value.
In our case, we use the involutory matrix given as follow:
3 11 9 4
10 9 6 10
A= 2 12 10 2
5 5 3 4
Table 2. Result of Mapping technique of pixels to points and the corresponding encrypted points.
VI. EXPRIMENTAL RESULTS
This section represents the simulation results illustrating the performance of the proposed encryption
algorithm. Netbeans is chosen as simulation software. Our algorithm has been validated using grayscale and
color images. The results of application of our algorithm on Lena image are given in Figures (Figure 4, Figure 5,
Figure 6, Figure 7).
Intensity
value
130 129 193 192 194 157 158 159
Mapping
point
(57, 30) (12, 17) (11, 48) (63, 67) (13, 5) (42, 17) (12, 56) (55, 22)
Encrypted
point
(52, 35) (6, 6) (19, 56) (44, 65) (47, 15) (60, 69) (62, 0) (50, 71)
6. Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve
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Figure 4. Layout of Proposed System
Figure 5. Select Input Image
7. Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve
www.ijeijournal.com Page | 14
Figure 6. Encrypted Image of “Lena image”.
Figure 7. Decrypted Image of “Lena image”.
In [13], the authors demonstrate that Hill cipher can’t encrypt the image properly if the image consists
of large area covered with same color and gray level. In our case, we have taken Lena image and encrypted it
using the proposed algorithm. The proposed method works for any images with different gray scale as well as
color images. The result in Figure 7 shows that the proposed method encrypt image properly as compared to the
original Hill cipher algorithm. Moreover, this total process of image-encryption has highly time efficient, and
secure, and gives a very simple and flexible approach.
The above algorithm is tested on the color image “FSTE”. Figure 8 and Figure 9 show result of
application of our algorithm on color image to obtain encrypted and decrypted images. Encrypted images
visually appear secure enough and decryption leads to successful retrieval of original image.
8. Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve
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Figure 8. Encrypted Image of “FSTE image”.
Figure 9. Decrypted Image of “FSTE image”.
VII. CONCLUSION
This paper introduced a new approach for image encryption using elliptic curve. In fact, the plain
image is divided into blocks: data matrix. The proposed cryptosystem uses a different key for mapping and
encryption process and the possibility of known plaintext attack is highly reduced as the key used changes with
every block and it is generated randomly using transformation algorithm based ECC. In this paper a new
mapping method introduced to convert an image pixel value to a point on a predefined elliptic curve over finite
field Fp using transformation algorithm. This mapping technique is very fast with low complexity and
9. Security Enhancement of Image Encryption Based on Matrix Approach using Elliptic Curve
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computation. This technique will results a high distribution of different points for repetitive intensity values. The
result shows that the proposed method is more secure to force attacks as compared to the original Hill cipher
algorithm. As a future work, the proposed cryptosystem can be extended for encrypting the video messages as
well as sound encryption process.
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