Iris Feature Extraction Based on the Fuzzy Clustering Evaluation Algorithm

Abstract:

In the iris recognition, as the texture feature of iris is complicated , and it is affected by the acquisition environment, time, condition and other factors, so it is difficult to express its complete information in single features of iris. Therefore, the combination of a variety of features or integration of expression and recognition method becomes a new kind of choice. Information integration concept originated in the 1970s. In recent years, because of the gradually in-depth recognition of people, the application of information integration technology in the pattern recognition becomes a hot spot of the research, especially when the single pattern cannot complete various aspects of requirements well in the pattern recognition, the adoption of integration technology can integrate various aspects of information provided by multi-pattern features, so as to obtain more comprehensive and accurate information of the recognized objects and overcome the limitations of recognition method through single-pattern feature, thus getting a satisfactory effect.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 3412-3415
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.3412
• Online since: May 2014
• Authors: Jin Liu*, Chang Ming Liu, Yan Jun Sun
• Keywords: Evaluation Model, Fuzzy Clustering, Fuzzy Mathematics

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