A Novel Dynamic Fingerprint Segmentation Method Based on Fuzzy C-Means and Genetic Algorithm

In automatic fingerprint identification system (AFIS), fingerprint segmentation plays a crucial role in improving detection accuracy and reducing the computation time of feature extraction. With the goal of refining performance of AFIS, in this paper, we investigate a novel dynamic fingerprint segme...

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Vydáno v:IEEE access Ročník 8; s. 132694 - 132702
Hlavní autoři: Lei, Wu, Lin, You
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Biological cells
cluster
Clustering algorithms
FCM
Feature extraction
Fingerprint recognition
Fingerprint segmentation
Fingerprinting
Fingerprints
genetic algorithm
Genetic algorithms
Heuristic algorithms
Histograms
Image segmentation
morphology
Post-processing
ISSN:2169-3536, 2169-3536
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Shrnutí:In automatic fingerprint identification system (AFIS), fingerprint segmentation plays a crucial role in improving detection accuracy and reducing the computation time of feature extraction. With the goal of refining performance of AFIS, in this paper, we investigate a novel dynamic fingerprint segmentation algorithm. The proposed algorithm is based on the existed dynamic image segmentation algorithm using fuzzy c-means (FCM) and genetic algorithm. Specifically, relying on different gray level of histogram and improved post-processing method, we establish a well-performed fingerprint segmentation system. The extensive results from our empirical experiments demonstrate the high performance of our proposed dynamic fingerprint segmentation algorithm, and its better performance than other competing approaches.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3011025