Scale parameter-estimating method for adaptive fingerprint pore extraction model

Yao Yi; Liangcai Cao; Wei Guo; Yaping Luo; Qingsheng He; Guofan Jin

doi:10.1117/12.907279

28 November 2011 Scale parameter-estimating method for adaptive fingerprint pore extraction model

Yao Yi, Liangcai Cao, Wei Guo, Yaping Luo, Qingsheng He, Guofan Jin

Proceedings Volume 8200, 2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 82001K (2011) https://doi.org/10.1117/12.907279
Event: International Conference on Optical Instruments and Technology (OIT2011), 2011, Beijing, Beijing, China

Abstract

Sweat pores and other level 3 features have been proven to provide more discriminatory information about fingerprint characteristics, which is useful for personal identification especially in law enforcement applications. With the advent of high resolution (≥1000 ppi) fingerprint scanning equipment, sweat pores are attracting increasing attention in automatic fingerprint identification system (AFIS), where the extraction of pores is a critical step. This paper presents a scale parameter-estimating method in filtering-based pore extraction procedure. Pores are manually extracted from a 1000 ppi grey-level fingerprint image. The size and orientation of each detected pore are extracted together with local ridge width and orientation. The quantitative relation between the pore parameters (size and orientation) and local image parameters (ridge width and orientation) is statistically obtained. The pores are extracted by filtering fingerprint image with the new pore model, whose parameters are determined by local image parameters and the statistically established relation. Experiments conducted on high resolution fingerprints indicate that the new pore model gives good performance in pore extraction.

Citation Download Citation

Yao Yi, Liangcai Cao, Wei Guo, Yaping Luo, Qingsheng He, and Guofan Jin "Scale parameter-estimating method for adaptive fingerprint pore extraction model", Proc. SPIE 8200, 2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 82001K (28 November 2011); https://doi.org/10.1117/12.907279

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KEYWORDS

Image filtering

Fingerprint recognition

Image segmentation

Image enhancement

Databases

Forensic science

Image processing

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