Anand R

Bio: Anand R is an academic researcher. The author has contributed to research in topics: Fingerprint recognition & Standard test image. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

FPGA Implementation of Fingerprint Recognition System using Adaptive Threshold Technique

Abstract: The real time fingerprint biometric system is implemented using FGPA. In this paper, we propose FPGA Implementation of Fingerprint Recognition System using Adaptive Threshold Technique with novel adaptive threshold for each person. The fingerprint images are considered from FVC2004 (DB3_A) and processed to resize fingerprint size to 256X256. The DWT is applied on fingerprint and considered only LL coefficients as features of fingerprint. The Adaptive Threshold value for each person is computed using Deviations between two successive samples of a person, Average Deviation, Standard Deviation and constant. The Adaptive Threshold for test image is computed using Deviations between test images and samples of database, Average Deviation, Standard Deviation and constant. If the Average Threshold of test image is less than Average Threshold of a person then it is considered as match else mismatched. It is observed that the success rate of identifying a person is high in the proposed method compared to existing techniques and also the device utilization in the proposed architecture is less compared to existing architectures.

FPGA implementation of image steganography using Haar DWT and modified LSB techniques

Abstract: Security places an important role in communication applications for secure data transfers. Image Steganography is one of the most reliable technique in encryption and decryption of an image (hidden) inside other image (cover) such way that only cover image is visible. In this paper frequency domain Image Steganography using DWT and Modified LSB technique is proposed. The proposed approach uses DWT to convert spatial domain information to frequency domain information. The LL band is used for further Image Steganographic process. The image is decoded using inverse LSB. Since the LL band is used for encoding and decoding purpose, memory requirement of the design is less for hardware implementation. Also this will increase the operating frequency of the architecture. The proposed technique obtains high PSNR for both stegano and recovered hidden image.

An Efficient FPGA based Background Subtraction Algorithm for Object Detection

Abstract: Object Detection is an integral part of security system where tracking accuracy and time plays a vital role. This makes moving object detection becomes one of the challenging tasks in current world scenario like video surveillance, traffic monitoring etc. In this paper, an efficient FPGA based Background Subtraction Algorithm for Object Detection is proposed. The process involves three stages of Pre-processing using median filter, Detection with background subtraction and Post-processing using Threshold technique. To achieve the optimum results of the total module, optimization is done at the architecture level of each block without affecting the accuracy of the processed data. The entire architecture is designed using VHDL language and implemented on Virtex-5 FPGA board. The comparison results prove that the proposed technique is more efficient than existing in terms of both hardware utilization and detection accuracy.

Secure Multimodal Biometric Recognition Based on Speech, Face and Fingerprint Using Feature Level Fusion Approach

Abstract: Biometric is the field for user authentication and verification as well as for providing security from unauthorized access. Various biometric traits have been utilized for development of secure model to provide security. Uni-modal biometric system has been designed to authorize user identity. These systems use single biometric traits that can be used for recognition process. Biometric traits are face, finger, iris, palm, vain and speech. On the basis of these systems authentication models have been prepared that can be used for user validation. The main problem in uni-modal biometric system is that due to use of single trait of biometric it is an easy process to capture biometric identification of individual. In recent research multimodal biometric authentication systems have been developed that can be used for authentication of the users. To overcome security threats in the proposed work face finger and voice based traits have been included to develop more accurate and secure system.