DocumentCode
3294450
Title
A new effective algorithm for iris location
Author
Lijun Zhou ; Yide Ma ; Jing Lian ; Zhaobin Wang
Author_Institution
Sch. of Sci. & Eng., Lanzhou Univ., Lanzhou, China
fYear
2013
fDate
12-14 Dec. 2013
Firstpage
1790
Lastpage
1795
Abstract
Iris location is an essential step and an important part in an iris recognition system. However, traditional iris location methods often involve a large space of search, which is calculation wasting and sensitive to noise. And these methods adopt circular orientation to locate the pupillary boundary; it may lead to inaccurate location result and influence the subsequent feature extraction and recognition. To address these problems, this paper presents a precise iris location algorithm based on Vector Field Convolution (VFC, an improved Snake model) to improve the accuracy of iris location. Firstly, obtaining the iris area completely include the inside and outside boundary from an original iris image, then using minimum average grey value method to determine initialization contour of VFC model automatically, so as to locate an iris inner boundary precisely under the internal and external force of active contour. At last, we adopt the improved Daugman algorithm to locate the iris outer boundary that relatively contains little texture information. Experimental results show that the location accuracy of this method is higher, the iris inner edge location is much closer to the real boundary, the result of location have been improved significantly.
Keywords
feature extraction; iris recognition; vectors; Daugman algorithm; Snake model; VFC; active contour; circular orientation; feature extraction; feature recognition; iris location; iris recognition system; minimum average grey value method; pupillary boundary; vector field convolution; Biomimetics; Conferences; Decision support systems; Robots; Daugman algorithm; Snake model; VFC model; iris location; minimum average grey value;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on
Conference_Location
Shenzhen
Type
conf
DOI
10.1109/ROBIO.2013.6739727
Filename
6739727
Link To Document