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Based On Characteristics Of Palm-line Palmprint Identification Method

Posted on:2007-11-19Degree:MasterType:Thesis
Country:ChinaCandidate:H XuFull Text:PDF
GTID:2208360185984005Subject:Pattern Recognition and Intelligent Systems
Abstract/Summary:PDF Full Text Request
As one of the most important biometrics features, palmprint with many strong points, such as simple sampling, one and only feature, information in abundance has significant influence on research. According to the character of palmprint, the dissertation proposes a largest inscribed circle based on positioning and segmentation method, which does not need basic preprocess, and does not need any contour detection and key points detection. The dissertation tries employing multiresolution image decomposition based on the 2-D morphological wavelet transform then. After morphological wavelet transform, rotation and translation compensation based on FFT is performed then. The eigenpalmprints are defined and applied them to identifying the online palmprints. At the end of the dissertation, a series of experiments are carried out to prove the feasibility of the preprocessing method and the recognition method. The main contents are as follows:1. The positioning and segmentation in online palmprint system is a basic and important job. According to the character of palmprint, the dissertation proposes a biggest inscribed circle based positioning and segmentation method, which does not need basic preprocess and does not need any contour detection and key points detection. This method is quite robust and can deal with more palmprint distortions. And the palmprint image's quality can not have influence on the method easily.2. Employing multiresolution image decomposition based on the 2-D morphological wavelet transform , based on the enhancement of the main principal features in a palmprint image, can not only wipe off fine ridges, but also minish the size of the original palmprint image, in order to speed up rotation and translation compensation based on FFT later.3. Rotation and translation compensation is the key issue for the feature matching and recognition. Rotation and translation compensation based on FFT is performed based on the 2-D morphological wavelet transform. In this dissertation, the rotation and translation compensation is an extension of the phase correlation technique...
Keywords/Search Tags:Inscribed Circle, Morphological Wavelet, Rotation and Translation Compensation, Eigenpalmprints, Palmprint Recognition
PDF Full Text Request
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