New method-feature extraction layer amalgamation for face and iris

Abstract

The invention relates to a new face-iris combination identifying method-characteristic layer extraction and combination. A face-iris characteristic extraction layer combining system is established according to nerve network, evolution calculation and fuzzy theory. For structure design, full and local geometry topological structure is adopted. A particle-group optimizing arithmetic is utilized to optimize network control parameters. When the characteristics of the face and the iris image are extracted, techniques of a super-resolution image reinforcing arithmetic, an illumination compensating arithmetic based on improved spherical harmonic function, gesture estimation based on linear relevant filters, Candide model based on a three-dimensional face and expression analysis based on an ASM arithmetic, etc., are adopted to robustly extract the eigenvectors of the face and the iris, and a self-developed double face-iris collecting device is also adopted to collect images of the face and the iris image. The method not only can establish a new system which is provided with learning capability and can automatically choose optimal network topological structure and automatically regulate net control parameters, but also can overcome and reduce the bad impacts of factors of environment and physiology, etc., during the extraction process to the independent characteristics of the face and the iris, thus effectively enhancing the identifying rate of the face-iris combination identification and promoting the system performance based on the face-iris combination identification to develop towards practical, reliable and acceptable directions.

Description

technical field [0001] The patent of this invention belongs to the technical fields of computational intelligence, pattern recognition and image processing. Based on the research on the single biometric recognition technology of human face and iris, the theory and algorithm of information fusion of human face and iris at the feature extraction layer are discussed. Background technique [0002] With the increasing requirements for the accuracy and reliability of social security and identity identification, the current single biometric identification system product cannot meet the needs of the society. Therefore, new models and algorithms should be studied to further improve the identification rate and reduce errors. The recognition rate and false rejection rate are still a development trend. In addition, the research and application of multi-modal biometric identification is gradually rising and deepening, which is an inevitable trend in the development of biometric identific...

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Problems solved by technology

[0002] With the increasing requirements for the accuracy and reliability of social security and identity identification, the current single biometric identification system product cannot meet the needs of the society. Therefore, new models and algorithms should be studied to further improve the identification rate and reduce errors. Recognition rate and false rejection rate are still a development trend

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