A Two-Level Matching Scheme for Speedy and Accurate Palmprint Identification

Li, Fang; Leung, M.K.H.; Yu, Xiaozhou

doi:10.1007/978-3-540-69429-8_33

Cited by 8 publications

(4 citation statements)

References 9 publications

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“…Figure 1 shows the flow chart of the system. The palmprint pre-processing and line feature extraction processes can be found in [10]. The matching method is the proposed relative angle-difference based Hausdorff distance, which is shown in Figure 2.…”

Section: System Overviewmentioning

confidence: 99%

Palmprint Matching using Pairwise Relative Angle Histogram

Leung

Sim

2007

2007 International Conference on Machine Learning and Cybernetics

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In this paper, we propose a novel approach to retrieve line-patterns from large databases in a rotation and translation invariant manner, at the same time, tackle broken line problem. Line segments are extracted from an image as primitives. Each local structure is represented by a set of pair-wise angle relationships, which are simple, invariant to translation and rotation, robust to end-point erosion, segment error, and sufficient for discrimination. Experiment showed encouraging results which also implicate that line segments could provide sufficient information for palmprint recognition.

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Section: System Overviewmentioning

confidence: 99%

Palmprint Matching using Pairwise Relative Angle Histogram

Leung

Sim

2007

2007 International Conference on Machine Learning and Cybernetics

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“…The conventional Daugman-like classifier uses global features enclosed by zerocrossing boundaries in the palmprint biometrics systems. In two-level palmprint matching scheme [23], the global features for coarse level filtering can be extracted by Hough transform and, for fine-level matching, the local features extracted from the localities and directions of the principal lines in the palmprint.…”

Section: Journal Of Applied Mathematicsmentioning

confidence: 99%

Palmprint Authentication System Based on Local and Global Feature Fusion Using DOST

Kumar¹,

Premalatha²

2014

Journal of Applied Mathematics

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Palmprint is the region between wrist and fingers. In this paper, a palmprint personal identification system is proposed based on the local and global information fusion. The local and global information is critical for the image observation based on the results of the relationship between physical stimuli and perceptions. The local features of the enhanced palmprint are extracted using discrete orthonormal Stockwell transform. The global feature is obtained by reducing the scale of discrete orthonormal Stockwell transform to infinity. The local and global matching distances of the two palmprint images are fused to get the final matching distance of the proposed scheme. The results show that the fusion of local and global features outperforms the existing works on the available three datasets.

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“…For iris matching, Sun et al [22,23] proposed a "cascade" system in which the first stage is a conventional Daugman-like classifier while the classifier at the second stage uses "global" features -areas enclosed by zero-crossing boundaries. In [24], the authors described a two-level palmprint matching scheme. For coarse-level filtering, Hough transform is used to extract global features; for fine-level matching, the local information extracted from the locations and orientations of individual lines is used.…”

Section: Introductionmentioning

confidence: 99%

Ensemble of local and global information for finger–knuckle-print recognition

Zhang

Zhu

2011

Pattern Recognition

186

108

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Abstract. Biometrics authentication is an effective method for automatically recognizing a person's identity. Recently, it has been found that the finger-knuckle-print (FKP), which refers to the inherent skin patterns of the outer surface around the phalangeal joint of one's finger, has high capability to discriminate different individuals, making it an emerging biometric identifier. In this paper, based on the results of psychophysics and neurophysiology studies that both local and global information is crucial for the image perception, we present an effective FKP recognition scheme by extracting and assembling local and global features of FKP images. Specifically, the orientation information

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A Two-Level Matching Scheme for Speedy and Accurate Palmprint Identification

Cited by 8 publications

References 9 publications

Palmprint Matching using Pairwise Relative Angle Histogram

Palmprint Matching using Pairwise Relative Angle Histogram

Palmprint Authentication System Based on Local and Global Feature Fusion Using DOST

Ensemble of local and global information for finger–knuckle-print recognition

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