Gabor human face recognizing method based on simplified intelligent single-particle optimizing algorithm

Abstract

The invention relates to a Gabor human face recognizing method based on a simplified intelligent single-particle optimizing algorithm, comprising a simplified intelligent single-particle optimizing algorithm and a link of selecting a Gabor filter group by the simplified intelligent single-particle optimizing algorithm, wherein the simplified intelligent single-particle optimizing algorithm comprises the following steps of: carrying out optimizing search on a solution space of a problem function by a particle and respectively carrying out intelligent updating on all dimensionality components of the single particle during iteration; and the link of selecting the Gabor filter group by the simplified intelligent single-particle optimizing algorithm comprises the following steps of: constructing a particle structure according to the quantity of Gabor filters, determining a particle search range and using a Fisher criterion as a fitness function; during the human face recognition, carrying out characteristic extraction on a human face image conforming to the authentication to form a characteristic database; after a new human face image is input, carrying out the characteristic extraction on the human face image by the selected Gabor filter; and comparing the obtained characteristic vector with the characteristics in the database by a minimal adjacent classifier to judge whether the input image is contained in the database or not and a corresponding identity. The invention improves the recognition precision and the characteristic extracting pertinence.

Description

technical field

[0001] The invention relates to the technical field of face image recognition, in particular to a Gabor face recognition method based on a simplified intelligent single-particle optimization algorithm. Background technique

[0002] With the continuous improvement of social informatization, the demand for personal identity authentication is increasing, and the original identification methods can no longer meet the requirements of accuracy and convenience. Then there is an identification method based on face images. The current face recognition methods are mainly divided into two categories: (1) the recognition method based on the overall pattern, which recognizes by studying the overall attributes of the face image pattern; (2) the recognition method based on feature analysis, which uses the face reference point Relative ratios and other parameters describing facial features constitute feature vectors, which are identified by comparison. A practical face rec...

Images