摘要：In some fields like forensic research, experts demand that a found sample of an individual can be matched with its full counterpart contained in a database. The found sample may present several characteristics that make this matching more difficult to perform, such as distortion and , most importantly, a very small size. Several solutions have been presented intending to solve this problem, however, big computational effort is required or low recognition rate is obtained. In this paper, we present a fast, simple, and efficient method to relate a small sample of a partial palmprint to a full one using elemental optimization processes and a voting mechanic. Experimen tation sho ws that our method performs with a higher recognition rate than the state of the art method , when trying to identify palmprint samples with a radius as small as 2.64 cm.
其他摘要：In some fields like forensic research, experts demand that a found sample of an individual can be matched with its full counterpart contained in a database. The found sample may present several characteristics that make this matching more difficult to perform, such as distortion and , most importantly, a very small size. Several solutions have been presented intending to solve this problem, however, big computational effort is required or low recognition rate is obtained. In this paper, we present a fast, simple, and efficient method to relate a small sample of a partial palmprint to a full one using elemental optimization processes and a voting mechanic. Experimen tation sho ws that our method performs with a higher recognition rate than the state of the art method , when trying to identify palmprint samples with a radius as small as 2.64 cm.
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