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Iris Location Method Based on Multi-line Fitting

Author: HuWanJun
Tutor: KongJun
School: Northeast Normal University
Course: Applied Computer Technology
Keywords: Iris authentication Eyelid detection Eyelash detection Hough transform Amount of information
CLC: TP391.41
Type: Master's thesis
Year: 2013
Downloads: 7
Quote: 0
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Abstract


With the development of the society, progress of science, information security becomes more important. At present, biometric technologies become an important research topic in the information security field, and the iris recognition is one of the research contents of the subject. In the iris recognition system, the existence of eyelids and eyelashes noises might generate negative effect on pattern analysis. Iris location accurately has become a key point in the biometric field.Since multiple lines can approximate a curve, this paper proposes a iris location method based on multi-line, makes detailed researches on the inner circle boundary and outer circle boundary of iris in the iris course detection section, which considers the edges and statistical feature adequately to detect the eyelids and eyelashes noises in the captured iris images. First, multi-scale edge detection is used to get the iris coarse locations, and rank filter is employed to smooth images for determining a more accurate searching area of eyelids. Second, morphological operations as well as line hough transform are presented to reserve the available edge points for multi-line eyelids fitting. Specially, the adaptive average intensity of individual iris image based on region of interest (ROI) is educed to get the statistical threshold for eyelashes detection.Kind of experiments has indicated that the proposed method can effectively remove the occlusion caused by eyelids and eyelashes, increase the amount of information (AOI) of segmented iris, improve the iris location accuracy, and make foundation for future research.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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