Effective Local Features Matching Based Rapid Iris Recognition with Interference Elimination Pre-processing for Identity Identification
Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering · 2019
In this paper, the effect ive local features matching based iris matching methods are developed for identity identification.To avoid the eyelid/eyelash interferences, the proposed interference elimination pre-processing scheme is effectively used to remove the image region due to the eyelid/eyelash obstruction, and the retrieved iris reg ion only locates near the pupil around the ring area for the recognition.The iris features are enhanced by the Contrast Limited Adaptive Histogram Equaliza t ion (CLAHE) and Gabor filtering processes.Then the efficient local features matching based technologies, i.e. the Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF) methods, are applied to the iris features matching.The local features matching technology uses the local features of images, and it keeps the feature invariance fo r the changes of rotation, scaling, and brightness.Finally, the Fast Library for Appro ximate Nearest Neighbors (FLANN) and the Random Samp le Consensus (RANSAC) algorith ms are used to increase the matching efficiency.By the similar iris database and the SIFT-based technologies, the proposed SIFTbased approach yields to better Correct Recognition Rate (CRR) and False Acceptance Rate (FA R) in comparison with the previous SIFT-based designs, where the CRR of the proposed design can be up to 97%.