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Shi C, Meijer JM, Guo J, Azzopardi G, Diercksr GF, Schmidt E, Zillikens D, Jonkman MF, Petkov N. Detection of u-serrated patterns in direct immunofluorescence images of autoimmune bullous diseases by inhibition-augmented COSFIRE filters. Int J Med Inform 2019; 122:27-36. [DOI: 10.1016/j.ijmedinf.2018.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Accepted: 11/20/2018] [Indexed: 10/27/2022]
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ZHANG WEIPENG, TANG YUANYAN, YOU XINGE. FINGERPRINT ENHANCEMENT USING WAVELET TRANSFORM COMBINED WITH GABOR FILTER. INT J PATTERN RECOGN 2011. [DOI: 10.1142/s0218001404003861] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The performance of automatic fingerprint identification system (AFIS) is heavily determined by the quality of the input image, thus an effective method to enhance the fingerprint image is essential in such a system. In this paper, we combine the filter-based method, which is mostly used nowadays with wavelet transform to achieve a more reliable and effective approach to fingerprint enhancement. This novel approach consists of five main steps, namely: (1) normalization, (2) decomposition, (3) wavelet coefficient adjustment, (4) Gabor filtering, and (5) reconstruction. Using this new method, a more clear fingerprint image can be obtained, which can distinctly improve the accuracy of the minutiae extraction module and finally achieve a better performance of the entire system. Experiments have been conducted in our study and positive experimental results have been received, which show that the proposed combined method is more effective and robust than other existing methods such as the filter-based and direct gray-level approaches.
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Affiliation(s)
- WEIPENG ZHANG
- Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong, P. R. China
- Institute of Machine Intelligence, Nankai University, Tianjin, P. R. China
| | - YUAN YAN TANG
- Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong, P. R. China
- Department of Computer Science, Chongqing University, Chongqing, P. R. China
| | - XINGE YOU
- Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong, P. R. China
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