DocumentCode :
595211
Title :
Visualizing vein patterns from color skin images based on image mapping for forensics analysis
Author :
Chaoying Tang ; Hengyi Zhang ; Kong, A.W. ; Craft, N.
Author_Institution :
Forensics & Security Lab., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
2387
Lastpage :
2390
Abstract :
Traditionally, it was difficult to use vein patterns in evidence images for forensic identification, because they were nearly invisible in color images. We proposed a computational method based on skin optics to uncover vein patterns from color images. However, its performance is dependent on the accuracy of the skin optical model. In this paper, we propose an algorithm based on image mapping to visualize vein patterns. It extracts information from a pair of synchronized color and near infrared (NIR) images, and uses a neural network (NN) to map RGB values to NIR intensities. In addition, an NN weight adjustment scheme is proposed to improve the robustness of the algorithm. The proposed algorithm was examined on a database with 300 pairs of color and NIR images collected from the forearms of 150 subjects. The automatic matching results from the proposed algorithm were better than those from our previous method, and comparable to the results from matching NIR images with NIR images.
Keywords :
data visualisation; forensic science; image colour analysis; image matching; image retrieval; law administration; neural nets; vein recognition; NIR intensities; NN weight adjustment scheme; RGB values; color skin images; evidence images; forensic identification; forensics analysis; image mapping; information extraction; law enforcement agents; near infrared images; neural network; personal identification; skin optical model; vein pattern visualization; Color; Forensics; Image color analysis; Optical imaging; Skin; Veins; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460646
Link To Document :
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