Study of Fingerprint Enhancement and Matching

Fingerprint is the oldest and popular form of bio-metric identification. Extract Minutiae is most used method for automatic fingerprint matching, every person fingerprint has some unique characteristics called minutiae. But studying the extract minutiae from the fingerprint images and matching it with database is depend on the image quality of finger impression. To make sure the performance of finger impression identification we have to robust the quality of fingerprint image by a suitable fingerprint enhancement algorithm. Here we work with a quick finger impression enhancement algorithm that improve the lucidity of valley and ridge structure based on estimated local orientation and frequency. After enhancement of sample fingerprint, sample fingerprint is matched with the database fingerprints, for that we had done feature extraction, minutiae representation and registration. But due to Spurious and missing minutiae the accuracy of fingerprint matching affected. We had done a detail relevant finger impression matching method build on the Shape Context descriptor, where the hybrid shape and orientation descriptor solve the problem. Hybrid shape descriptor filter out the unnatural minutia paring and ridge orientation descriptor improve the matching score. Matching score is generated and utilized for measuring the accuracy of execution of the proposed algorithm. Results demonstrated that the algorithm is exceptionally satisfactory for recognizing fingerprints acquired from diverse sources. Experimental results demonstrate enhancement algorithm also improves the matching accuracy

FINGERPRINT RECOGNITION SYSTEM

This project is to design a fingerprint recognition system for security purposes. It will also explore and suggest some solution to the improvement to the existing fingerprint system. Security system that uses a pin code or access card can be easily misused or mishandled. A pin code can be cracked using some hacker software while an access card can easily be stolen or misplaced. Thus, these security methods are very vulnerable to hackers and criminals. Instead, a fingerprint is unique to every person and due to the fact that no two people have the same fingerprint pattern, it makes the fingerprint a very good resource in a security system. The aim of this project is to focus on the concept and methodology of the fingerprint recognition system. By grasping the concept and method of the fingerprint recognition flow, a prototype is developed that will compare an input fingerprint with its predefined template. The system should be able to compare and decide if the input fingerprint is the same as the predefined template. The output of the first stage is a preprocessing stage. There are two stages involved in preprocessing which is the image enhancement and image skeletonization. Fourier transfonn and histogram equalization is utilized to enhance the low quality image to a better image so that the feature extraction process will run smoothly. The second stage of the project is to define the orientation, ROI extraction and minutia extraction. The matching sequence and the angle orientation problem were resolved

FINGERPRINT RECOGNITION SYSTEM

This project is to design a fingerprint recognition system for security purposes. It will also explore and suggest some solution to the improvement to the existing fingerprint system. Security system that uses a pin code or access card can be easily misused or mishandled. A pin code can be cracked using some hacker software while an access card can easily be stolen or misplaced. Thus, these security methods are very vulnerable to hackers and criminals. Instead, a fingerprint is unique to every person and due to the fact that no two people have the same fingerprint pattern, it makes the fingerprint a very good resource in a security system. The aim of this project is to focus on the concept and methodology of the fingerprint recognition system. By grasping the concept and method of the fingerprint recognition flow, a prototype is developed that will compare an input fingerprint with its predefined template. The system should be able to compare and decide if the input fingerprint is the same as the predefined template. The output of the first stage is a preprocessing stage. There are two stages involved in preprocessing which is the image enhancement and image skeletonization. Fourier transfonn and histogram equalization is utilized to enhance the low quality image to a better image so that the feature extraction process will run smoothly. The second stage of the project is to define the orientation, ROI extraction and minutia extraction. The matching sequence and the angle orientation problem were resolved