Palmprint identification using Log Transformation of Transform Domain Features

The Palmprint is an efficient physiological biometric trait to identify a person. In this paper we propose Palmprint Identification using Log Transformation of Transform Domain Features. The Region of Interest (ROI) of palmprint image is extracted using preprocessing. The KWT and DWT are applied on preprocessed image to generate features. The KWT and DWT features of test image and database images are compared using Euclidian distance to compute EER and TSR values. The EER and TSR values of KWT and DWT are fused using Log Transformation to get better performance parameters. It is observed that the values of performance parameters are better in the case of proposed algorithm compared to existing algorithms

An Efficient Reconfigurable Architecture for Fingerprint Recognition

The fingerprint identification is an efficient biometric technique to authenticate human beings in real-time Big Data Analytics. In this paper, we propose an efficient Finite State Machine (FSM) based reconfigurable architecture for fingerprint recognition. The fingerprint image is resized, and Compound Linear Binary Pattern (CLBP) is applied on fingerprint, followed by histogram to obtain histogram CLBP features. Discrete Wavelet Transform (DWT) Level 2 features are obtained by the same methodology. The novel matching score of CLBP is computed using histogram CLBP features of test image and fingerprint images in the database. Similarly, the DWT matching score is computed using DWT features of test image and fingerprint images in the database. Further, the matching scores of CLBP and DWT are fused with arithmetic equation using improvement factor. The performance parameters such as TSR (Total Success Rate), FAR (False Acceptance Rate), and FRR (False Rejection Rate) are computed using fusion scores with correlation matching technique for FVC2004 DB3 Database. The proposed fusion based VLSI architecture is synthesized on Virtex xc5vlx30T-3 FPGA board using Finite State Machine resulting in optimized parameters

Fingerprint verification based on dual transformation technique

The Fingerprint is used to authenticate a person for multiple applications. In this paper, we propose Fingerprint Verification Based on Dual Transformation (FVDT). The Fingerprint image size of 300*480 is segmented into four cells of each size 150*240. The DCT is applied on each cell to convert from spatial domain to frequency domain. One level DWT is applied on DCT coefficients to derive four sub bands such as LL, LH, HL and HH. The directional information features and the centre area features on LL sub bands are computed. The final feature vector set is formed by concatenating directional information features and centre area features. The matching between database fingerprint and test fingerprint is based on ED, SVM and RF. It is observed that TSR and FRR values are improved in the case of proposed algorithm compared to the existing algorithm

Performance analysis of different matrix decomposition methods on face recognition

Applications using face biometric are ubiquitous in various domains. We propose an efficient method using Discrete Wavelet Transform (DWT), Extended Directional Binary codes (EDBC), three matrix decompositions and Singular Value Decomposition (SVD) for face recognition. The combined effect of Schur, Hessenberg and QR matrix decompositions are utilized with existing algorithm. The discrimination power between two different persons is justified using Average Overall Deviation (AOD) parameter. Fused EDBC and SVD features are considered for performance calculation. City-block and Euclidean Distance (ED) measure is used for matching. Performance is improved on YALE, GTAV and ORL face databases compared with existing methods

A Secure Image Steganography using LSB, DCT and Compression Techniques on Raw Images

Steganography is an important area of research in recent years involving a number of applications. It is the science of embedding information into the cover image viz., text, video, and image (payload) without causing statistically significant modification to the cover image. The modern secure image steganography presents a challenging task of transferring the embedded information to the destination without being detected. In this paper we present an image based steganography that combines Least Significant Bit(LSB), Discrete Cosine Transform(DCT), and compression techniques on raw images to enhance the security of the payload. Initially, the LSB algorithm is used to embed the payload bits into the cover image to derive the stego-image. The stego-image is transformed from spatial domain to the frequency domain using DCT. Finally quantization and runlength coding algorithms are used for compressing the stego-image to enhance its security. It is observed that secure images with low MSE and BER are transferred without using any password, in comparison with earlier works

Template based Mole Detection for Face Recognition

Face recognition is used for personal identification. The Template based Mole Detection for Face Recognition (TBMDFR) algorithm is proposed to verify authentication of a person by detection and validation of prominent moles present in the skin region of a face. Normalized Cross Correlation (NCC) matching, complement of Gaussian template and skin segmen tation is used to identify and validate mole by fixing predefined NCC threshold values. It is observed that the NCC values of TBMDFR are much higher compared to the existing algorithms

A Quality Hybrid Service Discovery Protocol

Hybrid protocol combines the advantages of proactive and reactive routing in adhoc network. The routing is initially established with some proactively prospected routes and then serves the demand from additionally activated nodes through reactive flooding. In this paper we propose A Quality Hybrid Service Discovery Protocol (QHSDP) for discovering services. A broadcast mechanism is used to get the service and routing information of the nodes present inside the zone. The routing and service information reduces the packet flooding in the network hence reducing collision and increasing packet delivery efficiency. Reduced control packets in turn reduces the battery power consumption. A query message is bordercasted through the peripheral nodes to the nodes outside the zone. This makes the discovery procedure more sclable, hence increasing the node’s coverage and reducing the latency in the proposed technology compared to the existing technolog

Off-line Signature Verification Based on Fusion of Grid and Global Features Using Neural Networks

Signature is widely used and developed area of research for personal verification and authentication. In this paper Off-line Signature Verification Based on Fusion of Grid and Global Features Using Neural Networks (SVFGNN) is presented. The global and grid features are fused to generate set of features for the verification of signature. The test signature is compared with data base signatures based on the set of features and match/non match of signatures is decided with the help of Neural Network. The performance analysis is conducted on random, unskilled and skilled signature forgeries along with genuine signatures. It is observed that FAR and FRR results are improved in the proposed method compared to the existing algorithm