title: Modeling and analysis of local comprehensive minutia relation for fingerprint matching.
abstract: This paper introduces a robust fingerprint matching scheme based on the comprehensive minutia and the binary relation between minutiae. In the method, a fingerprint is represented as a graph, of which the comprehensive minutiae act as the vertex set and the local binary minutia relations provide the edge set. Then, the transformation-invariant and transformation-variant features are extracted from the binary relation. The transformation-invariant features are suitable to estimate the local matching probability, whereas the transformation-variant features are used to model the fingerprint rotation transformation with the adaptive Parzen window. Finally, the fingerprint matching is conducted with the variable bounded box method and iterative strategy. The experiments demonstrate that the proposed scheme is effective and robust in fingerprint alignment and matching.
authors.affiliation: Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China. xiaoguang.he@ia.ac.cn
authors.forename: Xiaoguang
authors.initials: X
authors.lastname: He
authors.forename: Jie
authors.initials: J
authors.lastname: Tian
authors.forename: Liang
authors.initials: L
authors.lastname: Li
authors.forename: Yuliang
authors.initials: Y
authors.lastname: He
authors.forename: Xin
authors.initials: X
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001699:Biometry / Q000379:methods*; D003878:Dermatoglyphics / Q000145:classification*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity