Image characteristic description method based on Gabor synthetic characteristic

Abstract

The invention relates to an image characteristic description method based on a Gabor synthetic characteristic, which comprises the following steps: a first step, acquiring and uploading a human face image signal; a second step, performing resolution adjustment and matrix expression of a face image; a third step, extracting an image characteristic; and a fourth step, synchronously outputting a processing result. According to the image characteristic description method, through using the amplitude part and the phase part which are converted by the Gabor wave filter, wherein the phase part comprises direction information in the Gabor filtering result, a certain characteristic discriminating meaning is realized; the filtering result of a Gabor wave filter set is sufficiently utilized; more abundant characteristic information is extracted for facilitating afterward identification; furthermore for aiming at a defect of averaging image blocks, different importance degrees of sub image blocks to the integral image are considered; and furthermore the face characteristic can be better described in combination with texture contribution degrees.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an image feature description method based on Gabor comprehensive features. Background technique [0002] In the prior art, the face image feature description method based on Gabor features has achieved very good results. However, in practical applications, complex lighting and different angles are often encountered, such as video surveillance, human-computer interaction, public security systems, and so on. Therefore, the research on complex lighting and face recognition from different angles has also become a research hotspot in recent years. At present, a variety of solutions have been proposed for the description of complex lighting face features in recent years. In summary, they are mainly divided into two categories. : [0003] 1. The global feature description based on Gabor features is performed on face images with complex lighting and different angle...

AI Technical Summary

Problems solved by technology

[0003] 1. The global feature description based on Gabor features is performed on face images with complex lighting and different angles. The main idea is to extract global features of the image. Some Gabor features only use the amplitude part of the Gabor filter transformation, without awareness and consideration of the phase information of the Gabor features that also play an important role in face description;

[0004] 2. Local Gabor feature description is performed on face images with complex lighting and different angles, aiming to describe the local features of the image to the greatest extent. This type of method has high stability and recognition rate for the description of face features, but The defect of this method is that it does not consider the contribution of each local feature to the overall description of the image, and it is considered that all local feature descriptions have the same contribution to the whole.

[0005] To sum up, the existing face feature description method based on Gabor feature does not make full use of the phase information of Gobor feature, and the phase of Gobor feature plays an important role in face feature description

In addition, insufficient consideration is given to the contribution of local features to the entire image, and there are defects and deficiencies such as poor classification and recognition effects and low stability, which cannot well meet the needs of practical applications.

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