School Debit Transaction Using Fingerprint Recognition System

This paper proposed a fingerprint based school debit transaction system using minutiae matching biometric technology. This biometric cashless transaction system intensely shortens the luncheon line traffic and labour force compared to conventional cash payment system. Furthermore, contrast with card cashless transaction system, fingerprint cashless transaction system with benefit that user need not carry additional identification object and remember lengthy password. The implementation of this cashless transaction system provides a more organize, reliable and efficient way to operate the school debit transaction system.

A Secured Contactless Fingerprint Verification Method Using a Minutiae Matching Technique

Most matching or verification phases of fingerprint systems use minutiae types and orientation angle to find matched minutiae pairs from the input and template fingerprints. Unfortunately, due to some non-linear distortions, like excessive pressure and fingers twisting during enrollment, this process can cause the minutiae features to be distorted from the original. The authors are interested in a fingerprint matching method using contactless images for fingerprint verification. After features extraction, they compute Euclidean distances between template minutiae (bifurcation and ending points) and input image minutiae. They compute then after bifurcation ridges orientation angles and ending point orientations. In the decision stage, they analyze the similarity between templates. The proposed algorithm has been tested on a set of 420 fingerprint images. The verification accuracy is found to be acceptable and the experimental results are promising. Future work will enhance the proposed verification method by a new template protection technique.

Enhanced Minutiae Extraction for High-Resolution Palmprint Recognition

A palmprint generally possesses about 10 times more minutiae features than a fingerprint, which could provide reliable biometric-based personal authentication. However, wide distribution of various creases in a palmprint creates a number of spurious minutiae. Precisely and efficiently, minutiae extraction is one of the most critical and challenging work for high-resolution palmprint recognition. In this paper, we propose a novel minutiae extraction and matching method for high-resolution palmprint images. The main contributions of this work include the following. First, a circle-boundary consistency is proposed to update the local ridge orientation of some abnormal points. Second, a lengthened Gabor filter is designed to better recover the discontinuous ridges corrupted by wide creases. Third, the principal ridge orientation of palmprint image is calculated to establish an angle alignment system, and coarse-to-fine shifting is performed to obtain the optimal coordinate translation parameters. Following these steps, minutiae matching can be efficiently performed. Experiment results conducted on the public high-resolution palmprint database validate the effectiveness of the proposed method.