Abstract
In this paper, a vein pattern extraction method is proposed for biometric purposes. First, we utilize a maximal intra-neighbor difference (MIND) vector of all pixels in the original image to represent the relationship between each pixel and its neighborhood. Based on the MIND vectorgram (MINDVG), we define a maximal intra-neighbor vector difference (MIVND) as an index to unveil the preliminary vein pattern. Finally, we use an adaptive threshold to extract the venation pattern. The advantage of this method is that, by combining the features of vein imaging and the spatial properties of the MINDVG, the algorithm can efficiently overcome the negative factors of inhomogeneous thickness and blurry boundaries in vein imaging without preprocessing. Experiments on several images show that this method can directly extract intact and clear vein patterns with minimal noise. Therefore, the proposed algorithm has been validated in vein pattern extraction.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
