This document presents a new approach for fingerprint matching called the Minutia Cylindrical Code (MCC) approach. It involves extracting minutia points from fingerprint images, then generating a code for each fingerprint based on the local structure and spatial relationships of minutia points within a cylindrical neighborhood. MCC codes make the fingerprints invariant to scale and rotation. The approach is tested on a database of 200 fingerprints and achieves false acceptance ratios between 6-13% and false rejection ratios below 0.12% depending on the threshold used. The MCC approach performs fingerprint matching efficiently while maintaining accuracy even when fingerprints are rotated or scaled.
A Comparative Study of Fingerprint Matching AlgorithmsIRJET Journal
This document summarizes and compares several fingerprint matching algorithms. It begins with an introduction to fingerprint-based identification and authentication, describing how fingerprints provide a unique biometric for verifying identity. The document then reviews three specific fingerprint matching algorithms: 1) Ratio of Relational Distance Matching, which uses minutiae points and distance ratios to match fingerprints; 2) K-Nearest Neighbor Minutiae Clustering, which clusters fingerprint graphs using KNN before matching; and 3) Minutiae Extraction and Matching Algorithm, which extracts minutiae points through a multi-step process of binarization, thinning, connecting, and margin increasing. The document concludes by noting each algorithm has advantages and disadvantages depending on the application
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.
Performance and analysis of improved unsharp masking algorithm for imageIAEME Publication
This document presents a study on improving an unsharp masking algorithm for image enhancement. It proposes using an exploratory data analysis model that decomposes an image into a model component and a residual component. The proposed algorithm then individually processes these components to increase contrast and sharpness while reducing halo effects and out-of-range issues. It defines new log-ratio operations for a generalized linear system using concepts from vector spaces and Bregman divergence to provide a theoretical basis for the algorithm. Experimental results showed the proposed algorithm enhanced contrast and sharpness better than previous methods.
This document provides a survey of various image segmentation techniques used in image processing. It begins with an introduction to image segmentation and its importance in fields like pattern recognition and medical imaging. It then categorizes and describes different segmentation approaches like edge-based, threshold-based, region-based, etc. The literature survey section summarizes several papers on specific segmentation algorithms or applications. It concludes with a table comparing the advantages and disadvantages of different segmentation techniques. The overall document aims to provide an overview of segmentation methods and their uses in computer vision.
Finger Print Image Compression for Extracting Texture Features and Reconstru...IOSR Journals
The document summarizes a method for fingerprint image compression that involves decomposing the image into two components - ridges (primary component) and textures/features (secondary component). The ridges are extracted and encoded using arithmetic coding combined with vector quantization, achieving a higher compression ratio than FBI standards. The decoding process reconstructs a hybrid surface based on the encoded ridges. The method allows for extracting minutiae directly from the compressed image without needing decompression, and provides both compression and the ability to reconstruct the original image. Experimental results show the compression ratio is better than FBI specified methods.
IRJET- Crowd Density Estimation using Image ProcessingIRJET Journal
This document describes a research project that uses image processing techniques to estimate crowd density. Specifically, it uses skin color detection and morphological operations to identify and count the number of people in an image. It begins with an abstract that introduces the topic and objectives. It then provides background information on relevant color models and traditional crowd density estimation approaches. The proposed system is described as using skin color detection in the HSV color space to identify skin pixels, followed by morphological operations to find and count human faces, in order to efficiently and accurately estimate crowd density in images.
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.
Region duplication forgery detection in digital imagesRupesh Ambatwad
Region duplication or copy move forgery is a common type of tampering scheme carried out to create a fake image. The field on blind image forensics depends upon the authenticity of the digital image. As in copy move forgery the duplicated region belongs to the same image, the detection of tampering is complex as it does not leave a visual clue. But the tampering gives rise to glitches at pixel level
A Comparative Study of Fingerprint Matching AlgorithmsIRJET Journal
This document summarizes and compares several fingerprint matching algorithms. It begins with an introduction to fingerprint-based identification and authentication, describing how fingerprints provide a unique biometric for verifying identity. The document then reviews three specific fingerprint matching algorithms: 1) Ratio of Relational Distance Matching, which uses minutiae points and distance ratios to match fingerprints; 2) K-Nearest Neighbor Minutiae Clustering, which clusters fingerprint graphs using KNN before matching; and 3) Minutiae Extraction and Matching Algorithm, which extracts minutiae points through a multi-step process of binarization, thinning, connecting, and margin increasing. The document concludes by noting each algorithm has advantages and disadvantages depending on the application
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.
Performance and analysis of improved unsharp masking algorithm for imageIAEME Publication
This document presents a study on improving an unsharp masking algorithm for image enhancement. It proposes using an exploratory data analysis model that decomposes an image into a model component and a residual component. The proposed algorithm then individually processes these components to increase contrast and sharpness while reducing halo effects and out-of-range issues. It defines new log-ratio operations for a generalized linear system using concepts from vector spaces and Bregman divergence to provide a theoretical basis for the algorithm. Experimental results showed the proposed algorithm enhanced contrast and sharpness better than previous methods.
This document provides a survey of various image segmentation techniques used in image processing. It begins with an introduction to image segmentation and its importance in fields like pattern recognition and medical imaging. It then categorizes and describes different segmentation approaches like edge-based, threshold-based, region-based, etc. The literature survey section summarizes several papers on specific segmentation algorithms or applications. It concludes with a table comparing the advantages and disadvantages of different segmentation techniques. The overall document aims to provide an overview of segmentation methods and their uses in computer vision.
Finger Print Image Compression for Extracting Texture Features and Reconstru...IOSR Journals
The document summarizes a method for fingerprint image compression that involves decomposing the image into two components - ridges (primary component) and textures/features (secondary component). The ridges are extracted and encoded using arithmetic coding combined with vector quantization, achieving a higher compression ratio than FBI standards. The decoding process reconstructs a hybrid surface based on the encoded ridges. The method allows for extracting minutiae directly from the compressed image without needing decompression, and provides both compression and the ability to reconstruct the original image. Experimental results show the compression ratio is better than FBI specified methods.
IRJET- Crowd Density Estimation using Image ProcessingIRJET Journal
This document describes a research project that uses image processing techniques to estimate crowd density. Specifically, it uses skin color detection and morphological operations to identify and count the number of people in an image. It begins with an abstract that introduces the topic and objectives. It then provides background information on relevant color models and traditional crowd density estimation approaches. The proposed system is described as using skin color detection in the HSV color space to identify skin pixels, followed by morphological operations to find and count human faces, in order to efficiently and accurately estimate crowd density in images.
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.
Region duplication forgery detection in digital imagesRupesh Ambatwad
Region duplication or copy move forgery is a common type of tampering scheme carried out to create a fake image. The field on blind image forensics depends upon the authenticity of the digital image. As in copy move forgery the duplicated region belongs to the same image, the detection of tampering is complex as it does not leave a visual clue. But the tampering gives rise to glitches at pixel level
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.
FACE RECOGNITION USING DIFFERENT LOCAL FEATURES WITH DIFFERENT DISTANCE TECHN...IJCSEIT Journal
A face recognition system using different local features with different distance measures is proposed in this
paper. Proposed method is fast and gives accurate detection. Feature vector is based on Eigen values,
Eigen vectors, and diagonal vectors of sub images. Images are partitioned into sub images to detect local
features. Sub partitions are rearranged into vertically and horizontally matrices. Eigen values, Eigenvector
and diagonal vectors are computed for these matrices. Global feature vector is generated for face
recognition. Experiments are performed on benchmark face YALE database. Results indicate that the
proposed method gives better recognition performance in terms of average recognized rate and retrieval
time compared to the existing methods.
SEMANTIC IMAGE RETRIEVAL USING MULTIPLE FEATUREScscpconf
In Content Based Image Retrieval (CBIR) some problem such as recognizing the similar
images, the need for databases, the semantic gap, and retrieving the desired images from huge
collections are the keys to improve. CBIR system analyzes the image content for indexing,
management, extraction and retrieval via low-level features such as color, texture and shape.
To achieve higher semantic performance, recent system seeks to combine the low-level features
of images with high-level features that conation perceptual information for human beings.
Performance improvements of indexing and retrieval play an important role for providing
advanced CBIR services. To overcome these above problems, a new query-by-image technique
using combination of multiple features is proposed. The proposed technique efficiently sifts through the dataset of images to retrieve semantically similar images.
Fuzzy Region Merging Using Fuzzy Similarity Measurement on Image Segmentation IJECEIAES
Some image’s regions have unbalance information, such as blurred contour, shade, and uneven brightness. Those regions are called as ambiguous regions. Ambiguous region cause problem during region merging process in interactive image segmentation because that region has double information, both as object and background. We proposed a new region merging strategy using fuzzy similarity measurement for image segmentation. The proposed method has four steps; the first step is initial segmentation using mean-shift algorithm. The second step is giving markers manually to indicate the object and background region. The third step is determining the fuzzy region or ambiguous region in the images. The last step is fuzzy region merging using fuzzy similarity measurement. The experimental results demonstrated that the proposed method is able to segment natural images and dental panoramic images successfully with the average value of misclassification error (ME) 1.96% and 5.47%, respectively.
This document summarizes a research paper that proposes a new method for detecting moving objects in videos using background subtraction and morphological techniques. The method establishes a reliable background updating model and uses dynamic thresholding to obtain a more complete segmentation of moving objects. The algorithm is implemented on a Microblaze soft processor in VHDL and tested on a Spartan-3 FPGA board. Experimental results show the area and speed of the algorithm. In conclusion, the proposed method allows inherently parallel processing of video frames and can improve detection accuracy by operating at the region level using morphological operations.
An efficient method for recognizing the low quality fingerprint verification ...IJCI JOURNAL
In this paper, we propose an efficient method to provide personal identification using fingerprint to get better accuracy even in noisy condition. The fingerprint matching based on the number of corresponding minutia pairings, has been in use for a long time, which is not very efficient for recognizing the low quality fingerprints. To overcome this problem, correlation technique is used. The correlation-based fingerprint verification system is capable of dealing with low quality images from which no minutiae can be extracted reliably and with fingerprints that suffer from non-uniform shape distortions, also in case of damaged and partial images. Orientation Field Methodology (OFM) has been used as a preprocessing module, and it converts the images into a field pattern based on the direction of the ridges, loops and bifurcations in the image of a fingerprint. The input image is then Cross Correlated (CC) with all the images in the cluster and the highest correlated image is taken as the output. The result gives a good recognition rate, as the proposed scheme uses Cross Correlation of Field Orientation (CCFO = OFM + CC) for fingerprint identification.
A new technique to fingerprint recognition based on partial windowAlexander Decker
1) The document presents a new technique for fingerprint recognition based on analyzing a partial window around the core point of a fingerprint.
2) The technique first locates the core point of a fingerprint, then determines a window around the core point. Features are extracted from this window and input into an artificial neural network (ANN) to recognize fingerprints.
3) The technique aims to reduce computation time for fingerprint recognition by focusing the analysis on a partial window rather than the whole fingerprint image.
A survey on efficient no reference blur estimation methodseSAT Journals
Abstract Blur estimation in image processing has come to be of great importance in assessing the quality of images. This work presents a survey of no-reference blur estimation methods. A no-reference method is particularly useful, when the input image used for blur estimation does not have an available corresponding reference image. This paper provides a comparison of the methodologies of four no-reference blur estimation methods. The first method applies a scale adaptive technique of blur estimation to get better accuracy in the results. The second blur metric involves finding the energy using second order derivatives of an image using derivative pair of quadrature filters. The third blur metric is based on the kurtosis measurement in the discrete dyadic wavelet transform (DDWT) of the images. The fourth method of blur estimation is obtained by finding the ratio of sum of the edge widths of all the detected edges to the total number of edges. The results provided are useful in comparing the methods based on metrics like Spearman correlation coefficient. The results are obtained by evaluation on images from the Laboratory for Image and Video Engineering (LIVE) database. The various methods are evaluated on the images by adding varying content of noise. The performance is evaluated for 3 different categories namely Gaussian blur, motion blur and also JPEG2000 compressed images. Blur estimation finds its application in quality assessment, image fusion and auto-focusing in images. The sharpness of an image can also be found from the blur metric as sharpness is inversely proportional to blur. Sharpness metrics can also be combined with other metrics to measure overall quality of the image. Keywords: Blur estimation, blur, no-reference
This document summarizes and compares four no-reference blur estimation methods: (1) a scale adaptive wavelet transform method, (2) a method using energy of quadrature filters, (3) a kurtosis measurement method using discrete dyadic wavelet transform, and (4) a method measuring average edge width. The methods are evaluated on blurred, noisy, and compressed images from a database. Results show the quadrature filter method performs best except for compressed images, where a perceptual method works best. The scale adaptive and kurtosis methods degrade more with noise while the quadrature filter method is more robust.
Features for Cross Spectral Image Matching: A SurveyjournalBEEI
This document summarizes several commonly used features for cross-spectral image matching between visible light and thermal images. It discusses how features represent information from different spectrum images for matching. The document reviews features such as local binary pattern (LBP), histogram of oriented gradients (HOG), scale-invariant feature transform (SIFT), Gabor wavelets, discrete cosine transform (DCT) and binary statistical image features (BSIF) that have been used in cross-spectral face and iris recognition with good results. It provides an overview of how these features extract unique characteristics from visible and thermal images to effectively represent the images and enable successful cross-spectral matching.
This document describes an image preprocessing scheme for line detection using the Hough transform in a mobile robot vision system. The preprocessing includes resizing images to 128x96 pixels, converting to grayscale, performing edge detection using Sobel filters, and edge thinning. A newly developed edge thinning method is found to produce images better suited for the Hough transform than other thinning methods. The preprocessed images are then used as input for line detection and the robot's self-navigation system.
Texture based feature extraction and object trackingPriyanka Goswami
This document provides a project report on texture-based feature extraction and object tracking. It discusses using various texture analysis techniques like Local Binary Pattern (LBP), Local Derivative Pattern (LDP), and Local Ternary Pattern (LTP) to extract features from images for tasks like cloud tracking. It implements these techniques in MATLAB and evaluates them on standard datasets to extract features and represent images with histograms for tasks like image recognition and analysis while reducing computational requirements compared to using raw images. The techniques are then applied to track cloud motion in weather satellite images by analyzing differences in texture histograms over time.
Image restoration based on morphological operationsijcseit
This document discusses image restoration using morphological operations. It begins with an abstract describing mathematical morphology and its applications to tasks like noise suppression, feature extraction, and image restoration. It then covers 6 morphological operations (erosion, dilation, opening, closing, boundary extraction, and region filling) and provides mathematical definitions and illustrations of their effects. Examples of applying these operations to grayscale images using different structuring element shapes are shown. The document concludes that morphological operations are effective for image restoration by applying dilation and erosion with the same factor to remove noise while retaining object shapes.
Generate a key for MAC Algorithm using Biometric Fingerprint ijasuc
known as cryptographic checksum or MAC that is appended to the message.
The unauthorized thefts in our society have made the requirement for reliable information security
mechanisms. Information security can be accomplished with the help of a prevailing tool like cryptography,
protecting the cryptographic keys is one of the significant issues to be deal with. Here we proposed a
biometric-crypto system which generates a cryptographic key from the Finger prints for calculating the
MAC value of the information we considered fingerprint because it is unique and permanent through out a
person’s life.
A novel embedded hybrid thinning algorithm forprjpublications
The document proposes a hybrid thinning algorithm that combines the Stentiford and Zhang-Suen thinning algorithms. It compares the hybrid algorithm to the original Stentiford and Zhang-Suen algorithms on an input image. The hybrid algorithm more accurately thins the image to a single pixel width but does not improve time complexity compared to the original algorithms. The hybrid approach uses four templates across two sub-iterations to identify and remove pixels based on connectivity values until no more can be removed. Experimental results show the hybrid algorithm more effectively increases image contrast than the original thinning algorithms.
SHORT LISTING LIKELY IMAGES USING PROPOSED MODIFIED-SIFT TOGETHER WITH CONVEN...ijfcstjournal
The paper proposes the modified-SIFT algorithm which will be a modified form of the scale invariant feature transform. The modification consists of considering successive groups of 8 rows of pixel, along the height of the image. These are used to construct 8 bin histograms for magnitude as well as orientation individually. As a result the number of feature descriptors is significantly less (95%) than the standard SIFT approach. Fewer feature descriptor leads to reduced accuracy. This reduction in accuracy is quite drastic when searching for a single (RANK1) image match; however accuracy improves if a band of likely (say tolerance of 10%) images is to be returned. The paper therefore proposes a two-stage-approach where
First Modified-SIFT is used to obtain a shortlisted band of likely images subsequently SIFT is applied within this band to find a perfect match. It may appear that this process is tedious however it provides a significant reduction in search time as compared to applying SIFT on the entire database. The minor reduction in accuracy can be offset by the considerable time gained while searching a large database. The
modified-SIFT algorithm when used in conjunction with a face cropping algorithm can also be used to find a match against disguised images.
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...IOSR Journals
This document describes a design of a Gabor filter for noise reduction in images of betel vine leaves to aid in disease segmentation. A Gabor filter is designed using Verilog HDL and implemented on a CADENCE platform. The filter takes pixel inputs from images that have undergone preprocessing like Sobel edge detection and segmentation. It convolves the pixels with stored filter coefficients to reduce noise and segment the diseased areas. The proposed Gabor filter achieves noiseless segmentation with increased speed and reduced delays compared to existing methods. It utilizes fewer resources with minimal warnings. The system could be enhanced further with 2D/3D processing and neural network training.
Extraction of texture features by using gabor filter in wheat crop disease de...eSAT Journals
This document discusses a method for detecting diseases in wheat crops using image processing and artificial neural networks. It involves taking digital images of wheat crop leaves and preprocessing the images by applying Gaussian and median filters to reduce noise. The images are then segmented using CIELAB color space. Texture features like area, perimeter, contrast, and energy are extracted from the images using Gabor filters. These features are then fed into an artificial neural network classifier to identify the type of disease present in the wheat crop. The method aims to help farmers more quickly and accurately detect diseases so they can better manage their crops and increase agricultural productivity.
This document discusses techniques for detecting digital image forgeries. It begins by defining different types of forgeries such as image retouching, splicing, and cloning. It then discusses mechanisms for forgery detection, distinguishing between active methods that embed hidden information in images and passive methods that analyze image traces. A key technique presented is using rotation angle estimation to detect cloned regions, with details on calculating variance to determine the rotation angle. The document concludes by presenting an algorithm for region duplication detection using hybrid wavelet transforms like DCT, Walsh, and Hadamard transforms.
This document reviews research on using computational fluid dynamics (CFD) to analyze coal/air flow in power plant pipelines in order to maintain uniform fuel feed rates at burners. Several studies are summarized that use CFD to simulate coal/air flow and model the effects of orifice flow restrictors placed in pipes. Correlations developed from CFD results relate pressure drop to factors like geometry, coal/gas loading ratio, and mass flux. CFD is shown to be an effective method for determining the optimal geometry and sizing of orifice flow restrictors to balance flow rates across burners.
This document describes the design of a tunable 3rd order Chebyshev low pass filter based on a floating inductor. The filter uses operational transconductance amplifiers (OTAs) to implement the floating inductor, floating resistor, and grounded resistor. The simulated floating inductor can be electronically tuned by varying the external bias current, which changes the transconductance of the OTAs. Simulation results show that the cutoff frequency of the filter can be adjusted by varying either the transconductance or bias current of the OTAs. The filter exhibits a maximum passband gain of 2.2 dB and a 3dB cutoff frequency of 7.1 MHz.
This document summarizes security issues and mechanisms related to online transactions. It discusses how online transactions work and outlines several common security threats like man-in-the-browser attacks, SQL injection, and phishing. It then describes security mechanisms used to protect online transactions, including biometrics, Secure Electronic Transactions protocol, anti-key logging technology, and WebPin technology. These security mechanisms aim to achieve goals like confidentiality, integrity, authentication and availability to make online transaction systems more secure.
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.
FACE RECOGNITION USING DIFFERENT LOCAL FEATURES WITH DIFFERENT DISTANCE TECHN...IJCSEIT Journal
A face recognition system using different local features with different distance measures is proposed in this
paper. Proposed method is fast and gives accurate detection. Feature vector is based on Eigen values,
Eigen vectors, and diagonal vectors of sub images. Images are partitioned into sub images to detect local
features. Sub partitions are rearranged into vertically and horizontally matrices. Eigen values, Eigenvector
and diagonal vectors are computed for these matrices. Global feature vector is generated for face
recognition. Experiments are performed on benchmark face YALE database. Results indicate that the
proposed method gives better recognition performance in terms of average recognized rate and retrieval
time compared to the existing methods.
SEMANTIC IMAGE RETRIEVAL USING MULTIPLE FEATUREScscpconf
In Content Based Image Retrieval (CBIR) some problem such as recognizing the similar
images, the need for databases, the semantic gap, and retrieving the desired images from huge
collections are the keys to improve. CBIR system analyzes the image content for indexing,
management, extraction and retrieval via low-level features such as color, texture and shape.
To achieve higher semantic performance, recent system seeks to combine the low-level features
of images with high-level features that conation perceptual information for human beings.
Performance improvements of indexing and retrieval play an important role for providing
advanced CBIR services. To overcome these above problems, a new query-by-image technique
using combination of multiple features is proposed. The proposed technique efficiently sifts through the dataset of images to retrieve semantically similar images.
Fuzzy Region Merging Using Fuzzy Similarity Measurement on Image Segmentation IJECEIAES
Some image’s regions have unbalance information, such as blurred contour, shade, and uneven brightness. Those regions are called as ambiguous regions. Ambiguous region cause problem during region merging process in interactive image segmentation because that region has double information, both as object and background. We proposed a new region merging strategy using fuzzy similarity measurement for image segmentation. The proposed method has four steps; the first step is initial segmentation using mean-shift algorithm. The second step is giving markers manually to indicate the object and background region. The third step is determining the fuzzy region or ambiguous region in the images. The last step is fuzzy region merging using fuzzy similarity measurement. The experimental results demonstrated that the proposed method is able to segment natural images and dental panoramic images successfully with the average value of misclassification error (ME) 1.96% and 5.47%, respectively.
This document summarizes a research paper that proposes a new method for detecting moving objects in videos using background subtraction and morphological techniques. The method establishes a reliable background updating model and uses dynamic thresholding to obtain a more complete segmentation of moving objects. The algorithm is implemented on a Microblaze soft processor in VHDL and tested on a Spartan-3 FPGA board. Experimental results show the area and speed of the algorithm. In conclusion, the proposed method allows inherently parallel processing of video frames and can improve detection accuracy by operating at the region level using morphological operations.
An efficient method for recognizing the low quality fingerprint verification ...IJCI JOURNAL
In this paper, we propose an efficient method to provide personal identification using fingerprint to get better accuracy even in noisy condition. The fingerprint matching based on the number of corresponding minutia pairings, has been in use for a long time, which is not very efficient for recognizing the low quality fingerprints. To overcome this problem, correlation technique is used. The correlation-based fingerprint verification system is capable of dealing with low quality images from which no minutiae can be extracted reliably and with fingerprints that suffer from non-uniform shape distortions, also in case of damaged and partial images. Orientation Field Methodology (OFM) has been used as a preprocessing module, and it converts the images into a field pattern based on the direction of the ridges, loops and bifurcations in the image of a fingerprint. The input image is then Cross Correlated (CC) with all the images in the cluster and the highest correlated image is taken as the output. The result gives a good recognition rate, as the proposed scheme uses Cross Correlation of Field Orientation (CCFO = OFM + CC) for fingerprint identification.
A new technique to fingerprint recognition based on partial windowAlexander Decker
1) The document presents a new technique for fingerprint recognition based on analyzing a partial window around the core point of a fingerprint.
2) The technique first locates the core point of a fingerprint, then determines a window around the core point. Features are extracted from this window and input into an artificial neural network (ANN) to recognize fingerprints.
3) The technique aims to reduce computation time for fingerprint recognition by focusing the analysis on a partial window rather than the whole fingerprint image.
A survey on efficient no reference blur estimation methodseSAT Journals
Abstract Blur estimation in image processing has come to be of great importance in assessing the quality of images. This work presents a survey of no-reference blur estimation methods. A no-reference method is particularly useful, when the input image used for blur estimation does not have an available corresponding reference image. This paper provides a comparison of the methodologies of four no-reference blur estimation methods. The first method applies a scale adaptive technique of blur estimation to get better accuracy in the results. The second blur metric involves finding the energy using second order derivatives of an image using derivative pair of quadrature filters. The third blur metric is based on the kurtosis measurement in the discrete dyadic wavelet transform (DDWT) of the images. The fourth method of blur estimation is obtained by finding the ratio of sum of the edge widths of all the detected edges to the total number of edges. The results provided are useful in comparing the methods based on metrics like Spearman correlation coefficient. The results are obtained by evaluation on images from the Laboratory for Image and Video Engineering (LIVE) database. The various methods are evaluated on the images by adding varying content of noise. The performance is evaluated for 3 different categories namely Gaussian blur, motion blur and also JPEG2000 compressed images. Blur estimation finds its application in quality assessment, image fusion and auto-focusing in images. The sharpness of an image can also be found from the blur metric as sharpness is inversely proportional to blur. Sharpness metrics can also be combined with other metrics to measure overall quality of the image. Keywords: Blur estimation, blur, no-reference
This document summarizes and compares four no-reference blur estimation methods: (1) a scale adaptive wavelet transform method, (2) a method using energy of quadrature filters, (3) a kurtosis measurement method using discrete dyadic wavelet transform, and (4) a method measuring average edge width. The methods are evaluated on blurred, noisy, and compressed images from a database. Results show the quadrature filter method performs best except for compressed images, where a perceptual method works best. The scale adaptive and kurtosis methods degrade more with noise while the quadrature filter method is more robust.
Features for Cross Spectral Image Matching: A SurveyjournalBEEI
This document summarizes several commonly used features for cross-spectral image matching between visible light and thermal images. It discusses how features represent information from different spectrum images for matching. The document reviews features such as local binary pattern (LBP), histogram of oriented gradients (HOG), scale-invariant feature transform (SIFT), Gabor wavelets, discrete cosine transform (DCT) and binary statistical image features (BSIF) that have been used in cross-spectral face and iris recognition with good results. It provides an overview of how these features extract unique characteristics from visible and thermal images to effectively represent the images and enable successful cross-spectral matching.
This document describes an image preprocessing scheme for line detection using the Hough transform in a mobile robot vision system. The preprocessing includes resizing images to 128x96 pixels, converting to grayscale, performing edge detection using Sobel filters, and edge thinning. A newly developed edge thinning method is found to produce images better suited for the Hough transform than other thinning methods. The preprocessed images are then used as input for line detection and the robot's self-navigation system.
Texture based feature extraction and object trackingPriyanka Goswami
This document provides a project report on texture-based feature extraction and object tracking. It discusses using various texture analysis techniques like Local Binary Pattern (LBP), Local Derivative Pattern (LDP), and Local Ternary Pattern (LTP) to extract features from images for tasks like cloud tracking. It implements these techniques in MATLAB and evaluates them on standard datasets to extract features and represent images with histograms for tasks like image recognition and analysis while reducing computational requirements compared to using raw images. The techniques are then applied to track cloud motion in weather satellite images by analyzing differences in texture histograms over time.
Image restoration based on morphological operationsijcseit
This document discusses image restoration using morphological operations. It begins with an abstract describing mathematical morphology and its applications to tasks like noise suppression, feature extraction, and image restoration. It then covers 6 morphological operations (erosion, dilation, opening, closing, boundary extraction, and region filling) and provides mathematical definitions and illustrations of their effects. Examples of applying these operations to grayscale images using different structuring element shapes are shown. The document concludes that morphological operations are effective for image restoration by applying dilation and erosion with the same factor to remove noise while retaining object shapes.
Generate a key for MAC Algorithm using Biometric Fingerprint ijasuc
known as cryptographic checksum or MAC that is appended to the message.
The unauthorized thefts in our society have made the requirement for reliable information security
mechanisms. Information security can be accomplished with the help of a prevailing tool like cryptography,
protecting the cryptographic keys is one of the significant issues to be deal with. Here we proposed a
biometric-crypto system which generates a cryptographic key from the Finger prints for calculating the
MAC value of the information we considered fingerprint because it is unique and permanent through out a
person’s life.
A novel embedded hybrid thinning algorithm forprjpublications
The document proposes a hybrid thinning algorithm that combines the Stentiford and Zhang-Suen thinning algorithms. It compares the hybrid algorithm to the original Stentiford and Zhang-Suen algorithms on an input image. The hybrid algorithm more accurately thins the image to a single pixel width but does not improve time complexity compared to the original algorithms. The hybrid approach uses four templates across two sub-iterations to identify and remove pixels based on connectivity values until no more can be removed. Experimental results show the hybrid algorithm more effectively increases image contrast than the original thinning algorithms.
SHORT LISTING LIKELY IMAGES USING PROPOSED MODIFIED-SIFT TOGETHER WITH CONVEN...ijfcstjournal
The paper proposes the modified-SIFT algorithm which will be a modified form of the scale invariant feature transform. The modification consists of considering successive groups of 8 rows of pixel, along the height of the image. These are used to construct 8 bin histograms for magnitude as well as orientation individually. As a result the number of feature descriptors is significantly less (95%) than the standard SIFT approach. Fewer feature descriptor leads to reduced accuracy. This reduction in accuracy is quite drastic when searching for a single (RANK1) image match; however accuracy improves if a band of likely (say tolerance of 10%) images is to be returned. The paper therefore proposes a two-stage-approach where
First Modified-SIFT is used to obtain a shortlisted band of likely images subsequently SIFT is applied within this band to find a perfect match. It may appear that this process is tedious however it provides a significant reduction in search time as compared to applying SIFT on the entire database. The minor reduction in accuracy can be offset by the considerable time gained while searching a large database. The
modified-SIFT algorithm when used in conjunction with a face cropping algorithm can also be used to find a match against disguised images.
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...IOSR Journals
This document describes a design of a Gabor filter for noise reduction in images of betel vine leaves to aid in disease segmentation. A Gabor filter is designed using Verilog HDL and implemented on a CADENCE platform. The filter takes pixel inputs from images that have undergone preprocessing like Sobel edge detection and segmentation. It convolves the pixels with stored filter coefficients to reduce noise and segment the diseased areas. The proposed Gabor filter achieves noiseless segmentation with increased speed and reduced delays compared to existing methods. It utilizes fewer resources with minimal warnings. The system could be enhanced further with 2D/3D processing and neural network training.
Extraction of texture features by using gabor filter in wheat crop disease de...eSAT Journals
This document discusses a method for detecting diseases in wheat crops using image processing and artificial neural networks. It involves taking digital images of wheat crop leaves and preprocessing the images by applying Gaussian and median filters to reduce noise. The images are then segmented using CIELAB color space. Texture features like area, perimeter, contrast, and energy are extracted from the images using Gabor filters. These features are then fed into an artificial neural network classifier to identify the type of disease present in the wheat crop. The method aims to help farmers more quickly and accurately detect diseases so they can better manage their crops and increase agricultural productivity.
This document discusses techniques for detecting digital image forgeries. It begins by defining different types of forgeries such as image retouching, splicing, and cloning. It then discusses mechanisms for forgery detection, distinguishing between active methods that embed hidden information in images and passive methods that analyze image traces. A key technique presented is using rotation angle estimation to detect cloned regions, with details on calculating variance to determine the rotation angle. The document concludes by presenting an algorithm for region duplication detection using hybrid wavelet transforms like DCT, Walsh, and Hadamard transforms.
This document reviews research on using computational fluid dynamics (CFD) to analyze coal/air flow in power plant pipelines in order to maintain uniform fuel feed rates at burners. Several studies are summarized that use CFD to simulate coal/air flow and model the effects of orifice flow restrictors placed in pipes. Correlations developed from CFD results relate pressure drop to factors like geometry, coal/gas loading ratio, and mass flux. CFD is shown to be an effective method for determining the optimal geometry and sizing of orifice flow restrictors to balance flow rates across burners.
This document describes the design of a tunable 3rd order Chebyshev low pass filter based on a floating inductor. The filter uses operational transconductance amplifiers (OTAs) to implement the floating inductor, floating resistor, and grounded resistor. The simulated floating inductor can be electronically tuned by varying the external bias current, which changes the transconductance of the OTAs. Simulation results show that the cutoff frequency of the filter can be adjusted by varying either the transconductance or bias current of the OTAs. The filter exhibits a maximum passband gain of 2.2 dB and a 3dB cutoff frequency of 7.1 MHz.
This document summarizes security issues and mechanisms related to online transactions. It discusses how online transactions work and outlines several common security threats like man-in-the-browser attacks, SQL injection, and phishing. It then describes security mechanisms used to protect online transactions, including biometrics, Secure Electronic Transactions protocol, anti-key logging technology, and WebPin technology. These security mechanisms aim to achieve goals like confidentiality, integrity, authentication and availability to make online transaction systems more secure.
This document discusses a proposed Smart Energy Distribution Management (SEDM) system that uses solar power and battery storage to help reduce power consumption. The SEDM controls power sockets using wireless communication based on the battery status and sets times for power usage. It can supply power from both the commercial grid and stored solar energy. The system prioritizes which devices to power based on preset battery level thresholds to make most efficient use of available energy. A hardware architecture is presented using a microcontroller, relays, wireless communication, and power monitoring to manage energy distribution from the solar and battery sources.
This document discusses various methods for selecting optimal input-output pairings for multivariable control systems. It begins with an introduction to the challenges of controlling multivariable systems and the importance of proper input-output pairing. It then reviews several pairing methods including the relative gain array (RGA), relative omega array, dynamic relative gain array, normalized RGA, and relative normalized gain array. It also discusses necessary conditions for decentralized integral controllability and presents rules for eliminating undesirable pairings to achieve this. Overall, the document provides an overview of established and newer techniques for analyzing interactions and selecting input-output pairs for multivariable processes.
This document summarizes research on modeling and analysis of magnetorheological (MR) fluid brakes. MR fluid brakes offer advantages over conventional brakes like fewer wearing parts and reduced stress. The document reviews past research on topics like preparation of MR fluids, rheological properties, and brake designs. It also outlines the scope for further research experiments involving varying properties of MR fluid components, supply current, motor speed, and gap between stator and rotor to analyze effects on braking torque. Key aspects of magnetic circuit and material selection for an MR brake design are discussed. The goal is to develop an innovative, smart brake system with digitally controllable braking torque using shear properties of MR fluids.
This document summarizes the generalized (G'/G)-expansion method for finding exact solutions to nonlinear partial differential equations with variable coefficients. It applies this method to derive new solutions to the shallow water wave equation with variable coefficients. Three types of solutions are obtained: hyperbolic function solutions when the discriminant is positive, trigonometric function solutions when the discriminant is negative, and rational solutions when the discriminant is zero. Graphs are provided to illustrate representative solutions from each case.
This document summarizes a research paper that proposes a technique for Gujarati handwritten character recognition using radial histogram feature extraction and Euclidean distance classification. The technique extracts 72 feature vectors from a character image by counting black pixels in radial directions at 5 degree intervals to create a radial histogram. Characters are classified by calculating the Euclidean distance between their feature vectors and pre-defined vectors for each character. The method achieves 26.86% accuracy on a database of Gujarati characters. While easy to implement, the radial histogram approach provides low accuracy due to similarities between characters and variability in handwriting styles.
This document summarizes research into the compressive strength of geopolymer mortar made with ground granulated blast furnace slag (GGBFS) and fly ash activated by a 14 molar sodium hydroxide and sodium silicate solution. Cubes of geopolymer mortar were produced with different percentages of GGBFS and tested for compressive strength at ages of 1, 3, and 7 days. The results showed that compressive strength increased with GGBFS percentage and age. The maximum 7-day strength of 32.67 MPa was achieved with 80% GGBFS and a fluid-to-binder ratio of 0.45. Below this ratio strength decreased, indicating 0.45 is the optimum
This document evaluates the performance of 20 radiation-based equations for estimating reference evapotranspiration (ET0) against the FAO Penman-Monteith method using 24 years of weather data from Pantnagar, India. The FAO24-Radiation method provided ET0 values that most closely matched the FAO Penman-Monteith method based on agreement index and RMSE values on daily, weekly, and monthly timescales. The Castaneda-Rao method estimated ET0 values that were almost equal to the FAO Penman-Monteith values. Overall, the FAO24-Radiation method performed the best among the 20 radiation-based equations evaluated for the sub-humid climate
This document summarizes a research paper on finding alternate paths in wireless networks using fast rerouting. It discusses how wireless ad hoc networks are self-configuring and nodes can join networks anywhere. Existing routing techniques have delays when links fail. The paper proposes calculating alternate paths instantly when a node fails to reduce packet loss. It would find a new path from the source to destination much faster than existing systems. When a node fails or does not respond, it would choose the next closest responding node and reroute packets along the new path immediately, without waiting for routing tables to update. This provides faster rerouting and recovery from link failures in wireless networks.
This document describes the installation and testing of a digital fuel indicator system that displays the amount of fuel in a vehicle's tank numerically (e.g. in liters or milliliters), rather than just bars. The system uses a float sensor connected to a variable resistor to detect the fuel level. An electronics kit with a microcontroller, ADC, and LCD display then processes the sensor output and calibrates it to display the fuel amount. The authors redesigned the irregularly shaped fuel tank to be rectangular for easier sensor installation. Their tests showed accurate readings down to 0.5 liters remaining, below which a buzzer was activated.
This document summarizes a study on the effect of soft stories in high-rise buildings. A soft story is one where the lateral stiffness is significantly less than the stories above, such as an open ground floor. Five analytical models of a 12-story reinforced concrete building were created with soft stories at different levels to investigate the structural response. The models were analyzed using SAP2000 software. Placement of the soft story, inclusion or removal of interior columns, and addition of shear walls were varied between models. Results such as displacements, drifts, and shears were compared to evaluate the impact of soft story location and design. The goal was to better understand soft story effects on seismic performance of high-rise structures.
This document discusses post-processing and rate distortion algorithms for the VP8 video codec. It first provides background on the need for post-processing algorithms to reduce blocking artifacts in compressed video, and for rate control algorithms to regulate bitrates and achieve high video quality within bandwidth constraints. It then summarizes existing in-loop deblocking filters and post-processing algorithms. A novel optimal post-processing/in-loop filtering algorithm is described that can achieve better performance than H.264/AVC or VP8 by computing optimal filter coefficients. Finally, a proposed rate distortion optimization algorithm for VP8 is discussed to improve its rate control and coding efficiency.
This document analyzes the Secure Electronic Transaction (SET) system for securing electronic payments. SET uses cryptography techniques like SSL and nested encryption tunnels to securely transmit payment information between customers, merchants, and payment gateways. The system aims to provide authentication, data confidentiality, non-repudiation, access control, and data integrity. It allows customers to securely purchase items online by encrypting transaction data and verifying identities. The main advantage is it protects payment information and can be easily used, without additional software, by securing the conventional communication channels used for online transactions.
This document summarizes an article from the International Journal of Research in Advent Technology about unmanned aerial vehicles (UAVs). It discusses the components and hardware required for small-scale UAV design, including EPP foam, transmitters/receivers, brushless motors, batteries, and servos. Applications of UAVs discussed include aerial surveillance, remote sensing, filmmaking, search and rescue, and inspecting infrastructure. The document also provides details on UAV system design, including the airframe, power plant, flight computer, avionics, and software.
This document summarizes a research paper that proposed a new framework for classifying driving patterns using smartphone sensors and a parameter-lite clustering technique. The framework uses accelerometer, gyroscope and GPS sensors on a smartphone placed in a vehicle to record driving data. It then applies a parameter-lite minimum spanning tree clustering algorithm to detect abnormal driving patterns without much user input. The results showed that the framework could accurately distinguish normal driving patterns from more aggressive maneuvers like sudden turns and driving over potholes. However, classifications of other patterns like lane changes or drowsy driving still need more testing. The aim is to help identify unsafe driving behaviors.
This document discusses analyzing data flow in wireless sensor networks. It first reviews routing techniques used in wireless sensor networks and how they differ based on the application. It then analyzes network reliability by examining link reliability and node energy availability. An expression is derived for instantaneous network reliability and mean time to failure. Simulation results are presented to validate the analysis. Requirements for different types of application data flows are reviewed, including low-bandwidth sensor readings, in-network flood modeling with bi-directional dynamic flows, and high-bandwidth image-based flow measurement. Packet-based and flow-based traffic measurement standards are also discussed.
This document discusses techniques for measuring fuel levels in vehicles. It begins by describing traditional float-based fuel level measurement systems and their accuracy limitations. It then outlines several alternative fuel level sensing techniques including capacitive sensing using electrodes, electronic load cells that measure weight, and ultrasonic sensing using sound waves. The document concludes that while traditional analog systems are cheap, digital techniques using sensors like these would provide more accurate readings and prevent fraud, benefiting both customers and manufacturers.
This document discusses a hand gesture recognition system for underprivileged individuals. It begins by outlining the key steps in hand gesture recognition systems: image capture, pre-processing, segmentation, feature extraction and gesture recognition. It then goes into more detail on specific techniques for each step, such as thresholding and edge detection for segmentation. The document also covers applications like access control, sign language translation and future areas like biometric authentication. In conclusion, it proposes that hand gesture recognition can help disabled individuals communicate through accessible human-computer interaction.
Stereo matching based on absolute differences for multiple objects detectionTELKOMNIKA JOURNAL
This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detion using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.
This document describes a new methodology for improving the accuracy of fingerprint verification systems. It proposes detecting singular points like core and delta points, and indexing templates based on the occurrence of delta points relative to the core point. Experiments on the FVC2006 database show the proposed method achieves higher recognition rates and lower false acceptance and rejection rates compared to existing minutiae-based matching techniques, especially for distorted images. It provides a concise way to represent templates and allows for faster matching by first comparing singular point information before minutiae points.
This document describes a new methodology for improving the accuracy of fingerprint verification systems. It proposes detecting singular points like core and delta points, and indexing templates based on the occurrence of delta points relative to the core point. Experiments on the FVC2006 database show the proposed method achieves higher recognition rates and lower false acceptance and rejection rates compared to existing minutiae-based matching techniques, especially for distorted images. It introduces a new way of storing templates as strings of numbers that encode singular point and minutiae information to enable faster matching.
Hybrid fingerprint matching algorithm for high accuracy and reliabilityeSAT 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.
Development of stereo matching algorithm based on sum of absolute RGB color d...IJECEIAES
This article presents local-based stereo matching algorithm which comprises a devel- opment of an algorithm using block matching and two edge preserving filters in the framework. Fundamentally, the matching process consists of several stages which will produce the disparity or depth map. The problem and most challenging work for matching process is to get an accurate corresponding point between two images. Hence, this article proposes an algorithm for stereo matching using improved Sum of Absolute RGB Differences (SAD), gradient matching and edge preserving filters. It is Bilateral Filter (BF) to surge up the accuracy. The SAD and gradient matching will be implemented at the first stage to get the preliminary corresponding result, then the BF works as an edge-preserving filter to remove the noise from the first stage. The second BF is used at the last stage to improve final disparity map and increase the object boundaries. The experimental analysis and validation are using the Middlebury standard benchmarking evaluation system. Based on the results, the proposed work is capable to increase the accuracy and to preserve the object edges. To make the proposed work more reliable with current available methods, the quantitative measurement has been made to compare with other existing methods and it shows the proposed work in this article perform much better.
NMS and Thresholding Architecture used for FPGA based Canny Edge Detector for...idescitation
In this paper, an architecture designed for Non-
Maximal Suppression used in Canny edge detection algorithm
is presented in order to reduce memory requirements
significantly. The architecture also achieves decreased latency
and increased throughput with no loss in edge detection. The
new algorithm used has a low-complexity 8-bin non-uniform
gradient magnitude histogram to compute block-based
hysteresis thresholds that are used by the Canny edge detector.
Furthermore, the hardware architecture of the proposed
algorithm is presented in this paper and the architecture is
synthesized on the Xilinx Virtex 5 FPGA. The design
development is done in VHDL and simulated results are
obtained using modelsim 6.3 with Xilinx 12.2.
This document summarizes a research paper that proposes an efficient method for recognizing low quality fingerprints using cross correlation. It begins with an introduction to fingerprint identification and verification. It then describes the proposed system, which uses orientation field methodology as a preprocessing step to convert images to orientation patterns. The input image is cross correlated with images in a cluster, and the highest correlated image is output. Experimental results on 1000 fingerprints from a public database showed the method achieved an 85% recognition rate. The paper concludes the cross correlation of orientation fields is an effective approach for fingerprint identification, especially for low quality images.
This document summarizes an analysis of iris recognition based on false acceptance rate (FAR) and false rejection rate (FRR) using the Hough transform. It first provides an overview of iris recognition and its typical stages: image acquisition, localization/segmentation, normalization, feature extraction, and pattern matching. It then describes existing methods used in each stage, including the Hough transform and rubber sheet model for localization and normalization. The proposed methodology applies Canny edge detection, Hough transform for boundary detection, normalization with the rubber sheet model, and calculates metrics like mean squared error, root mean squared error, signal-to-noise ratio, and root signal-to-noise ratio to evaluate the accuracy of iris recognition using FAR
A REVIEW ON LATENT FINGERPRINT RECONSTRUCTION METHODSIRJET Journal
This document reviews several methods for reconstructing latent fingerprints from minutiae points. It begins with an introduction to fingerprint features and representation. It then summarizes 10 research papers on latent fingerprint reconstruction methods. These include approaches using deep learning networks, fusion of minutiae and pore features, progressive feedback mechanisms, orientation field and phase reconstruction, and other techniques. The document concludes that while reconstruction methods have improved, there remains a performance gap when matching reconstructed prints to originals. The purpose is to provide a comparative analysis of existing latent fingerprint reconstruction methods.
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.
Image fusion using nsct denoising and target extraction for visual surveillanceeSAT 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.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document summarizes and compares various algorithms used to implement video surveillance systems, including pixel matching, image matching, and clustering algorithms. It first provides background on video surveillance systems and their need for automatic abnormal motion detection. It then reviews several specific algorithms: pixel matching, agglomerative clustering, reciprocal nearest neighbor pairing, sub-pixel mapping, patch matching, tone mapping, and k-means clustering. For each algorithm, it provides a brief overview of the approach and complexity. The document also discusses image matching algorithms like classic image checking, pixel-based identity checking, and pixel-based similarity checking. Overall, the document analyzes algorithms that can be used to detect and classify motion in video surveillance systems.
Stereo matching algorithm using census transform and segment tree for depth e...TELKOMNIKA JOURNAL
This article proposes an algorithm for stereo matching corresponding process that will be used in many applications such as augmented reality, autonomous vehicle navigation and surface reconstruction. Basically, the proposed framework in this article is developed through a series of functions. The final result from this framework is disparity map which this map has the information of depth estimation. Fundamentally, the framework input is the stereo image which represents left and right images respectively. The proposed algorithm in this article has four steps in total, which starts with the matching cost computation using census transform, cost aggregation utilizes segment-tree, optimization using winner-takes-all (WTA) strategy, and post-processing stage uses weighted median filter. Based on the experimental results from the standard benchmarking evaluation system from the Middlebury, the disparity map results produce an average low noise error at 9.68% for nonocc error and 18.9% for all error attributes. On average, it performs far better and very competitive with other available methods from the benchmark system.
Mislaid character analysis using 2-dimensional discrete wavelet transform for...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
This document discusses the implementation of a fingerprint matching algorithm. It begins with an introduction to fingerprint recognition and matching. It then discusses the literature on fingerprint matching algorithms. The proposed algorithm involves three main steps: fingerprint pre-processing (including enhancement and binarization), minutiae extraction, and post-processing (including false minutiae removal). Experimental results on the FVC2002 database show that the proposed algorithm has a lower matching time and better accuracy rates compared to an existing method. The algorithm is concluded to be effective for fingerprint image identification.
Matching algorithm performance analysis for autocalibration method of stereo ...TELKOMNIKA JOURNAL
Stereo vision is one of the interesting research topics in the computer vision field. Two cameras are used to generate a disparity map, resulting in the depth estimation. Camera calibration is the most important step in stereo vision. The calibration step is used to generate an intrinsic parameter of each camera to get a better disparity map. In general, the calibration process is done manually by using a chessboard pattern, but this process is an exhausting task. Self-calibration is an important ability required to overcome this problem. Self-calibration required a robust and good matching algorithm to find the key feature between images as reference. The purpose of this paper is to analyze the performance of three matching algorithms for the autocalibration process. The matching algorithms used in this research are SIFT, SURF, and ORB. The result shows that SIFT performs better than other methods.
Segmentation and recognition of handwritten digit numeral string using a mult...ijfcstjournal
In this paper, the use of Multi-Layer Perceptron (MLP) Neural Network model is proposed for recognizing
unconstrained offline handwritten Numeral strings. The Numeral strings are segmented and isolated
numerals are obtained using a connected component labeling (CCL) algorithm approach. The structural
part of the models has been modeled using a Multilayer Perceptron Neural Network. This paper also
presents a new technique to remove slope and slant from handwritten numeral string and to normalize the
size of text images and classify with supervised learning methods. Experimental results on a database of
102 numeral string patterns written by 3 different people show that a recognition rate of 99.7% is obtained
on independent digits contained in the numeral string of digits includes both the skewed and slant data.
This document presents a methodology for real-time object tracking using a webcam. It combines Prewitt edge detection for object detection and Kalman filtering for tracking. Prewitt edge detection is used to detect the edges of the moving object in each video frame. Then, Kalman filtering is used to track the detected object across subsequent frames by predicting its location. Experiments show the approach can efficiently track objects under deformation, occlusion, and can track multiple objects simultaneously. The combination of Prewitt edge detection and Kalman filtering provides an effective method for real-time object tracking.
07 18sep 7983 10108-1-ed an edge edit ariIAESIJEECS
Edge exposure or edge detection is an important and classical study of the medical field and computer vision. Caliber Fuzzy C-means (CFCM) clustering Algorithm for edge detection depends on the selection of initial cluster center value. This endeavor to put in order a collection of pixels into a cluster, such that a pixel within the cluster must be more comparable to every other pixel. Using CFCM techniques first cluster the BSDS image, next the clustered image is given as an input to the basic canny edge detection algorithm. The application of new parameters with fewer operations for CFCM is fruitful. According to the calculation, a result acquired by using CFCM clustering function divides the image into four clusters in common. The proposed method is evidently robust into the modification of fuzzy c-means and canny algorithm. The convergence of this algorithm is very speedy compare to the entire edge detection algorithms. The consequences of this proposed algorithm make enhanced edge detection and better result than any other traditional image edge detection techniques.
This document summarizes a research paper that examines pricing strategy in a two-stage supply chain consisting of a supplier and retailer. The supplier offers a credit period to the retailer, who then offers credit to customers. A mathematical model is formulated to maximize total profit for the integrated supply chain system. The model considers three cases based on the relative lengths of the credit periods offered at each stage. Equations are developed to represent the profit functions for the supplier, retailer and overall system in each case. The goal is to determine the optimal selling price that maximizes total integrated profit.
The document discusses melanoma skin cancer detection using a computer-aided diagnosis system based on dermoscopic images. It begins with an introduction to skin cancer and melanoma. It then reviews existing literature on automated melanoma detection systems that use techniques like image preprocessing, segmentation, feature extraction and classification. Features extracted in other studies include asymmetry, border irregularity, color, diameter and texture-based features. The proposed system collects dermoscopic images and performs preprocessing, segmentation, extracts 9 features based on the ABCD rule, and classifies images using a neural network classifier to detect melanoma. It aims to develop an automated diagnosis system to eliminate invasive biopsy procedures.
This document summarizes various techniques for image segmentation that have been studied and proposed in previous research. It discusses edge-based, threshold-based, region-based, clustering-based, and other common segmentation methods. It also reviews applications of segmentation in medical imaging, plant disease detection, and other fields. While no single technique can segment all images perfectly, hybrid and adaptive methods combining multiple approaches may provide better results. Overall, image segmentation remains an important but challenging task in digital image processing and computer vision.
This document presents a test for detecting a single upper outlier in a sample from a Johnson SB distribution when the parameters of the distribution are unknown. The test statistic proposed is based on maximum likelihood estimates of the four parameters (location, scale, and two shape) of the Johnson SB distribution. Critical values of the test statistic are obtained through simulation for different sample sizes. The performance of the test is investigated through simulation, showing it performs well at detecting outliers when the contaminant observation represents a large shift from the original distribution parameters. An example application to census data is also provided.
This document summarizes a research paper that proposes a portable device called the "Disha Device" to improve women's safety. The device has features like live location tracking, audio/video recording, automatic messaging to emergency contacts, a buzzer, flashlight, and pepper spray. It is designed using an Arduino microcontroller connected to GPS and GSM modules. When the button is pressed, it sends an alert message with the woman's location, sets off an alarm, activates the flashlight and pepper spray for self-defense. The goal is to provide women a compact, one-click safety system to help them escape dangerous situations or call for help with just a single press of a button.
- The document describes a study that constructed physical fitness norms for female students attending social welfare schools in Andhra Pradesh, India.
- Researchers tested 339 students in classes 6-10 on speed, strength, agility and flexibility tests. Tests included 50m run, bend and reach, medicine ball throw, broad jump, shuttle run, and vertical jump.
- The results showed that 9th class students had the best average time for the 50m run. 10th class students had the highest flexibility on average. Strength and performance generally improved with increased class level.
This document summarizes research on downdraft gasification of biomass. It discusses how downdraft gasifiers effectively convert solid biomass into a combustible producer gas. The gasification process involves pyrolysis and reactions between hot char and gases that produce CO, H2, and CH4. Downdraft gasifiers are well-suited for biomass gasification due to their simple design and ability to manage the gasification process with low tar production. The document also reviews previous studies on gasifier configuration upgrades and their impact on performance, and the principles of downdraft gasifier operation.
This document summarizes the design and manufacturing of a twin spindle drilling attachment. Key points:
- The attachment allows a drilling machine to simultaneously drill two holes in a single setting, improving productivity over a single spindle setup.
- It uses a sun and planet gear arrangement to transmit power from the main spindle to two drilling spindles.
- Components like gears, shafts, and housing were designed using Creo software and manufactured. Drill chucks, bearings, and bits were purchased.
- The attachment was assembled and installed on a vertical drilling machine. It is aimed at improving productivity in mass production applications by combining two drilling operations into one setup.
The document presents a comparative study of different gantry girder profiles for various crane capacities and gantry spans. Bending moments, shear forces, and section properties are calculated and tabulated for 'I'-section with top and bottom plates, symmetrical plate girder, 'I'-section with 'C'-section top flange, plate girder with rolled 'C'-section top flange, and unsymmetrical plate girder sections. Graphs of steel weight required per meter length are presented. The 'I'-section with 'C'-section top flange profile is found to be optimized for biaxial bending but rolled sections may not be available for all spans.
This document summarizes research on analyzing the first ply failure of laminated composite skew plates under concentrated load using finite element analysis. It first describes how a finite element model was developed using shell elements to analyze skew plates of varying skew angles, laminations, and boundary conditions. Three failure criteria (maximum stress, maximum strain, Tsai-Wu) were used to evaluate first ply failure loads. The minimum load from the criteria was taken as the governing failure load. The research aims to determine the effects of various parameters on first ply failure loads and validate the numerical approach through benchmark problems.
This document summarizes a study that investigated the larvicidal effects of Aegle marmelos (bael tree) leaf extracts on Aedes aegypti mosquitoes. Specifically, it assessed the efficacy of methanol extracts from A. marmelos leaves in killing A. aegypti larvae (at the third instar stage) and altering their midgut proteins. The study found that the leaf extract achieved 50% larval mortality (LC50) at a concentration of 49 ppm. Proteomic analysis of larval midguts revealed changes in protein expression levels after exposure to the extract, suggesting its bioactive compounds can disrupt the midgut. The aim is to identify specific inhibitor proteins in the midg
This document presents a system for classifying electrocardiogram (ECG) signals using a convolutional neural network (CNN). The system first preprocesses raw ECG data by removing noise and segmenting the signals. It then uses a CNN to extract features directly from the ECG data and classify arrhythmias without requiring complex feature engineering. The CNN architecture contains 11 convolutional layers and is optimized using techniques like batch normalization and dropout. The system was tested on ECG datasets and achieved classification accuracy of over 93%, demonstrating its effectiveness at automated ECG classification.
This document presents a new algorithm for extracting and summarizing news from online newspapers. The algorithm first extracts news related to the topic using keyword matching. It then distinguishes different types of news about the same topic. A term frequency-based summarization method is used to generate summaries. Sentences are scored based on term frequency and the highest scoring sentences are selected for the summary. The algorithm was evaluated on news datasets from various newspapers and showed good performance in intrinsic evaluation metrics like precision, recall and F-score. Thus, the proposed method can effectively extract and summarize online news for a given keyword or topic.
1. International Journal of Research in Advent Technology, Vol.3, No.6, June 2015
E-ISSN: 2321-9637
32
Minutia Cylindrical Code Based Approach for
Fingerprint Matching
Dilip Tamboli1
, Mr.Sandeep B Patil 2
, Dr.G.R.Sinha 3
1
P.G. Scholar, Department of Electronics & Telecommunication Engg. SSGI Bhilai, C.G.India
2
P.G. Scholar, Department of Electronics & Telecommunication Engg. SSGI Bhilai, C.G.India2
3
Assosiate Director & Prof., Department of Electronics & Telecommunication Engg. SSGI Bhilai, C.G.India3
diliptamboli_123@yahoo.com
1
, Patilsandeepb1212@gmail.com
2
,drgrsinha@ssgi.edu.in3
Abstract- Impression from the fingers and its matching is one of the important task of law enforcing body.
Minutia extraction from the fingerprint image decides the accuracy of the matching. Method presented in this
paper is also very efficient in matching the algorithm. Minutia cylindrical code(MCC) which is local descriptor
of the fingerprint image is used for matching the fingerprint image. MCC, codes the local direction and distance
between the minutia and hence invariants to the scale and rotation. False Acceptance ratio (FAR) and False
Rejection ration(FRR) is also computed to test the accuracy of the proposed method.
Index Terms- Minutia, FFT, MCC, Euclidean distance
1. INTRODUCTION
Recognition of fingerprint is one of the complicated
pattern recognition problems which is being studied
for the last 40 years.
Though various efficient algorithm have been
designed for fingerprint matching, it cannot be
concluded that this problem has solved. Accuracy,
interoperability and computational efficient algorithm
are still an open issue [1] in fingerprinting matching.
Most of the current fingerprint matching algorithms
are based on the minutia. Special ridge pattern are
called minutia. Ridge ending and ridge bifurcation are
some of the minutia.
In the past, minutia matching is considered as the two
dimensional pattern matching problem for aligning the
two minutia pair. This forced the researcher to find all
the possible transformation for two minutia matching.
Hough transform is one of the solution of this
problem[2][3]. High computational cost and lack of
robustness are some the problems of the global
minutia matching algorithm.
In the last few years, these problem is addressed by
introducing the local minutia descriptor and its
matching.
The characteristics of the local minutia descriptor is
such that it is invariants to the global transformation
and therefore appropriate for matching without the
need of global alignment.
Since local minutia descriptor based matching is based
on the arrangement of the local property therefore it
excludes the global feature and give better results.
Global matching algorithms have some of the benefits
which is not possible in case of local descriptor based
matching and hence an hybrid approach can be applied
to get the benefit of both the algorithm.
In this types of approach, first of all the local structure
is used to match the minutia quickly and robustly. In
the next step, matching at global level is performed for
validation purpose.
The evaluation of the minutia matching based on the
local structure passed in three stages. Stage one
correspond to the earlier approach in which local
structure are formed by considering the minutia lies
inside some regions. In this approach no global
validation was performed [4][5]. The approach
adopted by the [6] and [7] comes in the second stage.
[6] and [7] were the first to establishe a relationship
between minutia and its neighbourhood in term of
invariant angle distance and structure. In this stage,
global validation was also performed .
Third stage comprises of the method proposed by
Jiang and Yau[6] and Ratha [7]. These methods are
variants of the method proposed by the same author.
In this phase they extend the feature set of the
fingerpring by incorporating local ridge, local
frequency, shape its. [1] contain the exhaustive review
in fingerprint matching and recognition. For further
reference reader may go through the
[8]-[33].
Two types of local minutia structure were proposed.
First one is based on the nearest neighbourhood while
the other one is based on the fixed radius. In the
nearest neighbourhood [6] approach, centre minutia is
characterized by the K- closest minutia which are
spatially arranged. This gives the fixed length
descriptor which can be matched very efficiently. The
later approach is given by the [7]. In this approach,
neighbours are defined as the all the neighbours which
are inside the radius R of the centre minutia. In this
approach, the length of the descriptor is not fixed
making it difficult to match the fingerprint locally. But
this approach shows better tolerant against missing
and spurious minutia.
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2. PROPOSED METHODOLOGY
In this paper local descriptor based fingerprint
recognition is presented. Minutia cylinder code is used
as local descriptor. Block diagram of proposed
methodology is shown in figure 2.
First of all, with the help of scanner, Fingerprint image
of the input finger is registered. Minutia extraction
block is used to extract out the minutia from the
image.
With the help of minutia, a cylindrical code for
minutia is formed. Minutia cylindrical code represent
minutia local structure of the minutia distribution.
Once, minutia cylindrical code is generated for each
finger print then a database is created which contain
the minutia cylindrical codes of all the fingerprint
image. The last step of this method is matching or
testing. Next section describe the functioning of last
four block of this algorithm.
Fig.1 Basic Flow Diagram of Proposed Method
2.1. Minutia Extraction Process
In any fingerprint recognition system, Minutia
extraction is one of the important phase because the
performance of any fingerprint recognition system
depends on the how accurately minutia are extracted.
In this algorithm following steps have been adopted
for minutia extraction.
2.2 FP Image Enhancement
First step in any fingerprint recognition system is the
enhancement of the fingerprint image. This step is
adopted to improve the quality of the fingerprint
image so that all the minutia points become more clear
and extraction of the minutia points become easier.
Generally, Fingerprint image obtained by the
fingerprint scanner is noisy and of poor contrast.
Ridge and furrows are not visible due to the poor
contrast. Image enhancement increase the contrast of
ridge and furrows and also joined some of the broken
line which occurred in fingerprint image due to sensor
deficiency.
2.3 Histogram equalization
Histogram equalization basically adjust the intensity
distribution of the histogram and with this approach it
improve the global contrast of the image. This step
helps the lower contrast region to gain a higher
contrast while keeping the global contrast intact. This
method basically spread out the most frequently
occurred intensity value. Figure 3 represent the
histogram before and after applying histogram
equalization.
2.4 Fast Fourier Transform.
This process is accomplished for connecting the ridge
broken line . In this process first of all, Fingerprint
image is divided in to a block of 32 * 32 pixel and
then Fourier transform of this block is computed using
following formula.
for u = 0, 1, 2, ..., 31 and v = 0, 1, 2, ..., 31.
2.5 Image Binarization
This process is performed to convert the 8-bit gary
image to 1 bit image. In this, 0 represent the ridge and
1 represent the furrows. This step highlight the ridge
and furrows clearly in the image. A local adaptive
binarization method is used for this purpose.
2.6 Fingerprint Segmentation
This process is accomplished to extract out the region
of interest from the fingerprint image. In fingerprint
image, some of the area is not useful and carry
insignificant ridge and furrows. It is necessary to
discard this area . Segmentation process consist of two
Finger
Finger print
Scanner
Minutia
Extraction
Minutia Cylindrical code formation
Database Creation
Matching Algorithm
Fingerprint
Registration
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part i.e. Estimation of block direction, extraction of
region of interest by applying morphological
operation.
2.7 Estimation of Block Diagram
Block direction estimation is performed to separate
out background and foreground information. In finger
print image, foreground is represented by the ridges
and furrows while the background represent the no
information.
In order to compute the block diagram estimation, a
block of 16 *16 pixel is chosen and then block
direction is computed by using below mentioned
formula
tan2ß =
here
gx= Gradient along x-direction
gy= Gradient along y-direction
Certainity level for each block is then computed using
formula-
E =
Here
W= size of block (i.e. 16 in this case)
The value of E is compared with the threshold value to
decide whether the block comes under the
background( if E<threshold) or foreground (i.e if
E>threshold).
2.8 Morphological Operation for ROI extraction
In the last step morphological operation “opening” and
“closing” is applied to to extract the region of interest.
2.8.1 Ridge Thinning
This operation is applied to make the ridge width 1
pixel wide. This is performed by thinning operation.
2.8.2Minutia Marking
Next step is applied to mark the minutia by
applying a 3*3 window.
2.8.3False Minutia Removal
Inter-ridge distance is used for eliminating the false
minutia points which may affect the over all accuracy
of the fingerprint recognition system.
2.8.4Minutia Marking
At the final step each true minutia is marked with
three element. i.e. x-coordinate, y-coordinate and the
minutia direction or angle.
2.9 Minutia Cylindrical Code Information
Once the minutia information is obtained then the next
step is to form the minutia cylindrical code. In minutia
cylindrical code, a cylinder with 6 different layer is
used to represent the relative direction and distance
among different minutia. One such cylinder is shown
in figure 3.
Figure 3 represent the cylinder associated with the
minutia m={xm, ym, θm}. Radius of the cylinder is R
and xm and ym is the center of this cylinder. As
shown in the figure, a cuboid encloses the cylinder
whose base is aligned as per the direction of the
minutia i.e θm. The cuboid is divided in to a cell
where
The size and height of each cell is × and
respectively.
Where
Fig.2 Minutia Cylinder
Each cell of the cylinder can be accessed by three
coordinate i.e. i, j, k which represent the position of
the cell inside the cylinder. The value of i and j is
between 1 and Ns while the k takes the value between
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1 to Nd. The height k of the cylinder represent the
angle which is represented by the
If
Represent the centre of the cell having indices i,j.
In MCC, the contribution of each minutia for
each cell is computed and is given by
Which is computed by the spatial contribution
and directional contribution
Where spatial contribution is given by
And directional contribution is given by
And
Is the neighbourhood of the .
Here is the neighbourhood radius and ds (p, m)
represent the Euclidean distance between minutia m
and point p as shown in the figure given below-
Fig.3 Neighbourhood Radius
Once the MCC for all the fingerprint image is
obtained then a database of MCC is created.
2.10 Fingerprint Matching
In order to match the two fingerprint MCC, Euclidean
distance is computed between two fingerprint MCC as
given in the below
Where
= MCC of the testing fingerprint image
= MCC of the database.
MCC for each fingerprint image is rotation and scale
invariants therefore it gives better result in even if the
fingerprint image is rotated or scaled.
The database MCC for which the value of Ed is less
than the certain threshold is considered as the
matching one and corresponding fingerprint image is
considered as the matching image
3. EXPERIMENTAL RESULTS
A database of fingerprint images comprises of the
200 different fingerprint images are created for testing
the performance of the proposed method. A simulation
program is designed with the help of MATLAB ver
2009B. The simulation program is tested in a
core2duo processor computer with 2GB RAM.
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Fig.4 Original Fingerprint Image
Figure 5 display the original fingerprint image while
figure 6 display the extracted minutia points of the
fingerprint image.
Fig.5 Extracted Minutia Points in fingerprint image
In order to evaluate the performance of this method,
statistical measure like FAR(False acceptance Ratio)
and FRR(False rejection ratio) is also computed and
tabulated in table 1.
Fr AR is computed using following formula
Table 1 FAR and FRR for different value of
Threshold (Without Rotation)
Threshold Value FAR(in %) FRR(in %)
6 6.9 0.07
7 7.4 0.05
8 9.2 0.05
9 11.9 0.03
10 13.1 0.02
Table2 FAR and FRR of rotated fingerprint image
for different value of Threshold
Threshold Value FAR(in %) FRR(in %)
6 6.3 0.12
7 7.6 0.08
8 10.1 0.07
9 12.1 0.03
10 13.9 0.03
Fig.6 Minutia Cylindrical Code of the fingerprint
image shown in figure 5
4. CONCLUSION
Since from its inception, finger-print matching area
has been in the search of some robust technique for
matching the fingerprint accurately. The requirement
of rotation , scale invariants re the need of the hour. In
this paper a MCC based fingerprint matching
algorithm is implemented and presented. The
performance of the proposed system is satisfactory as
clear from the table 1. Even after rotating and scaling
the fingerprint, proposed system is able to achieve
good accuracy.
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