Abstract
Minutiae extraction is often carried out on thinned images. Thinning is a time-consuming process and causes undesired spikes and breaks. In this paper, a minutiae-extracting method is presented by encoding run-length code from binary images without a thinning process. Ridges in fingerprint images are represented as a cascade of runs, and minutiae detection has been accomplished by searching for starting or ending runs and merging or splitting runs. Experimental results show that the proposed method is fairly reliable and fast, when compared to a thinning-based method.
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Shin, JH., Hwang, HY., Chien, SI. (2003). Minutiae Extraction from Fingerprint Images Using Run-Length Code. In: Zhong, N., Raś, Z.W., Tsumoto, S., Suzuki, E. (eds) Foundations of Intelligent Systems. ISMIS 2003. Lecture Notes in Computer Science(), vol 2871. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39592-8_81
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DOI: https://doi.org/10.1007/978-3-540-39592-8_81
Publisher Name: Springer, Berlin, Heidelberg
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