Recognition of lip prints using Fuzzy c-Means clustering

• Autorzy: Wrobel K. , Froelich W.
• Języki publikacji: EN

Abstrakty

EN

In this paper a new method for lip print recognition is proposed. The proposed approach is based on Fuzzy c-Means clustering of the characteristics features of lip prints. First, the Hough transform is applied for the recognition of the characteristic features within lip prints, then Fuzzy c-Means clustering is performed to cluster those features. The proposed algorithm applies the results of clustering to find an unknown image withing the collected repository of lip prints. Instead of comparing all pairs of individual characteristic features, the proposed algorithm uses the representatives of clusters for the comparison of images. The advantage of using the proposed method is its increased tolerance to the noise in data and thus the increased efficiency of the recognition. The effectiveness of presented method has been verified experimentally using real-world images. The results are satisfactory and suggest the possibility of using the method in forensic identification systems

Słowa kluczowe

EN

lip print; image processing; clustering techniques; data classification

PL

grafika wargowa; przetwarzanie obrazu; metody grupowania; klasyfikacja danych

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2015
• Tom: Vol. 24
• Strony: 67--73
• Opis fizyczny: Bibliogr. 23 poz., rys., wykr.

Twórcy

autor

Wrobel K.

• Institute of Computer Science, University of Silesia, ul. Bedzinska 39, 41-200 Sosnowiec, Poland

autor

Froelich W.

• Institute of Computer Science, University of Silesia, ul. Bedzinska 39, 41-200 Sosnowiec, Poland

Bibliografia

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