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