Image enhancement in simple fingerprint minutiae extraction algorithm using crossing number on valley structure
In fingerprint recognition system, fingerprint feature extraction algorithm requires good quality fingerprint images to produce good results. Therefore, one step in the preprocessing stage is image enhancement to improve the quality of poor fingerprint image, so the minutiae points can be detected with good results. In this paper, we present how this enhancement process in simple minutiae detection algorithm using crossing number on valley structure improves detection of true minutiae.
Performance evaluation of simple fingerprint minutiae extraction algorithm using crossing number on valley structure
In fingerprint recognition system, performance of fingerprint feature extraction algorithm is important. We use visual analysis to evaluate this performance. 100 respondents fill a questionnaire consisting of 30 images from fingerprint feature extraction process. We get 12,3 % minutiae points missed by this algorithm. With BOZORTH3 minutiae matching algorithm, the distribution of matching score of 80-fingerprint images are presented and we obtain EER 5.89 % at threshold value 180.
Improvement of Fingerprint Sensor Reading Using FPGA Devices
In order to realize fingerprint recognition system in real time environment, we describe in this paper signal controller to read fingerprint sensor generated in FPGA devices. Basically this signal is generated using state machine. The simulation result for behavioral simulation and signal generation read by logic analyzer are presented in this paper. Initialization and reading time for 76800 pixels are 50.99 mS. It is faster than fingerprint sensor using USB connection, which is more than 250 ms.
Simple Fingerprint Minutiae Extraction Algorithm Using Crossing Number On Valley Structure
Most of the existing fingerprint extraction techniques currently available are based on ridge structure. The ridge usually has thicker structure than the valley, so that more processing time is needed to extract the ridge than extracting the valley. Taking the advantage of the thin structure of the valley, we proposed an algorithm that reduces the time needed for minutiae extraction. The algorithm was developed in Matlab environment using fingerprint images from FVC2004. In order to show the performance of the algorithm, numerical results are presented.