Browsing by Author "Liu, Limin"

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A Reliable Fingerprint Orientation Estimation Algorithm
(2011-01-01)
Liu, Limin
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Dai, Tian-Shyr
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
Correctly estimating fingerprint ridge orientation is an important task in fingerprint image processing. A successful orientation estimation algorithm can drastically improve the performance of tasks such as fingerprint enhancement, classification, and singular points extraction. Gradient-based orientation estimation algorithms are widely adopted in academic literature, but they cannot guarantee the correctness of ridge orientations. Even worse, they assign orientations to blocks with singular points. A novel and reliable orientation estimation algorithm is proposed in this paper. This algorithm runs in two phases. The first phase assigns reliable orientations to blocks with parallel structures and marks other blocks with noise, singular points, and minutiae as uncertain. Since most uncertain blocks marked in the first phase do have unique ridge orientations, the second phase of our algorithm restores the orientations of these uncertain blocks from their neighbor blocks orientations. Different from other orientation estimation algorithms, our algorithm leaves the blocks containing singular points and assigns reliable orientations to the other blocks. Detailed examples are given in this paper to show how our algorithm works. We use NIST-4 fingerprint database in our experiment to verify the superiority of our algorithm.
Ridge orientation estimation and verification algorithm for fingerprint enhancement
(2006)
Liu, Limin
;
Dai, Tian-Shyr
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Fingerprint image enhancement is a common and critical step in fingerprint recognition systems. To enhance the images, most of the existing enhancement algorithms use filtering techniques that can be categorized into isotropic and anisotropic according to the filter kernel. Isotropic filtering can properly preserve features on the input images but can hardly improve the quality of the images. On the other hand, anisotropic filtering can effectively remove noise from the image but only when a reliable orientation is provided. In this paper, we propose a ridge orientation estimation and verification algorithm which can not only generate an orientation of ridge flows, but also verify its reliability. Experimental results show that, on average, over 51 percent of an image in the NIST-4 database has reliable orientations. Based on this algorithm, a hybrid fingerprint enhancement algorithm is developed which applies isotropic filtering on regions without reliable orientations and anisotropic filtering on regions with reliable orientations. Experimental results show the proposed algorithm can combine advantages of both isotropic and anisotropic filtering techniques and generally improve the quality of fingerprint images.