Fingerprint indexing is an efficient technique that greatly improves the performance of automated fingerprint identification systems. We propose a continuous fingerprint indexing method based on location, direction estimation and correlation of fingerprint singular points. Location and direction estimation are achieved simultaneously by applying a T-shape model to directional field of fingerprint images. The T-shape model analyzes homocentric sectors around the candidate singular points to find lateral-axes and further main-axes. Then a distortion-tolerant filter of minimum average correlation energy is utilized to obtain a correlation-based similarity measure which gives the evidence of searching priority. The experiment is performed by 400-fingerprint retrieval from 10,000 templates and the mean search space is only 3.46% of the whole dataset.


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    Titel :

    Fingerprint indexing based on singular point correlation


    Beteiligte:
    Tong Liu, (Autor:in) / Guocai Zhu, (Autor:in) / Chao Zhang, (Autor:in) / Pengwei Hao, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    377816 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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