Abstract
This paper describes an embedded minutia-based matching algorithm using the reference point neighborhoods minutiae. The proposed matching algorithm is implemented in restricted environments such as smart card devices requiring careful monitoring of both memory and processing time usage. The proposed algorithm uses a circular tessellation to encode fingerprint features in neighborhood minutia localization binary codes. The objective of the present study is the development of a new matching approach which reduces both computing time and required space memory for fingerprint matching on Java Card. The main advantage of our approach is avoiding the implicit alignment of fingerprint images during the matching process while improving the fingerprint verification accuracy. Tests carried out on the public fingerprint databases DB1-a and DB2-a of FVC2002 have shown the effectiveness of our approach.
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