Paper
21 May 1993 Hierarchical fuzzy approach for fingerprint processing
Siavash Khorsandi, Anastasios N. Venetsanopoulos
Author Affiliations +
Proceedings Volume 1902, Nonlinear Image Processing IV; (1993) https://doi.org/10.1117/12.144757
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States
Abstract
The approach presented in this paper is a procedure for detecting local pattern orientation of fingerprint images. Also, it is a reliable method for detecting singular points of these images. A fingerprint is a directional image consisting of many ridges in different directions and its structural information lies in the position and direction of its constituent ridges. The core part of a fingerprint processing system is detecting local ridges orientations which is done by using some directional operators. The area of support of these operators is a major concern. Using a large area, details of flow deflection are not sensed and with a small area of support, the direction is not detected correctly because of existing noise in the image. To take advantage of both small and large area sizes, we consider several area sizes in a hierarchical order. Starting with a large area size, the pattern orientation is detected at every block of the image and is used to validate and correct the direction of smaller subblocks in the next level of the hierarchy. This procedure continues until obtaining reliable pattern directions at sufficiently small blocks. We shall also address the problem of detecting singular points of fingerprints and shall show that they are detected correctly and accurately using this hierarchical approach.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Siavash Khorsandi and Anastasios N. Venetsanopoulos "Hierarchical fuzzy approach for fingerprint processing", Proc. SPIE 1902, Nonlinear Image Processing IV, (21 May 1993); https://doi.org/10.1117/12.144757
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Cited by 1 scholarly publication.
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KEYWORDS
Fuzzy logic

Nonlinear image processing

Image filtering

Ridge detection

Detection and tracking algorithms

Image segmentation

Nonlinear filtering

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