Title: A new method for automatic extraction of region of interest from infrared images of dorsal hand vein pattern based on floating selection model
Authors: Ali Nozari Pour; Ehsan Eslami; Javad Haddadnia
Addresses: Department of Electrical/Computer Engineering, Hakim University, Sabzevar, Iran ' Department of Electrical/Computer Engineering, Khorasan University, Mashhad, Iran ' Department of Electrical/Computer Engineering, Hakim University, Sabzevar, Iran
Abstract: Personal identification based on vein pattern is one of the latest biometric approaches that have ever attracted lots of attentions. The method of personal identification suggested in this study utilises the individual's dorsal hand vein pattern. However, hand spin and relocation in different trials of image acquisition is a limiting factor in application of this approach. We introduce a new procedure for automatic selection of region of interest (ROI) designated 'floating ROI' in which adjusting the lengths and angles of sides in the ROI quadrant, the imaging process stays resistant against any hand relocation. Moreover, a new method for the vein pattern extraction called 'square thresholding' is introduced that greatly improves the extraction of vein-patterns. For this, the average of grey level of the pixels in a 5 × 5 neighbourhood is compared with 9 × 9 neighbourhood for any pixel. To verify validity of the proposed methods, 1,200 images taken from 100 individuals is used. As a result, an identification rate with the accuracy of 96.41% is obtained.
Keywords: personal identification; biometrics; dorsal hand veins; pattern recognition; region of interest; ROI extraction; thresholding; wavelet transform; artificial neutral networks; ANNs; automatic extraction; infrared images; floating selection; hand vein patterns; pattern extraction.
International Journal of Applied Pattern Recognition, 2015 Vol.2 No.2, pp.111 - 127
Received: 05 May 2014
Accepted: 19 Aug 2014
Published online: 22 May 2015 *