Improved Gabor filter is used to the training samples,and gets the face feature vector groups;In the detection step,firstly,the characteristics of intensity in eye region and symmetry in face were used for finding face candidates,and all the candidates were verified by improved Gabor filter to confirm the face or not.

It extracts texture features of handwriting image by multi-channel Gabor filters and makes classification by most neighboring classifier.

Image texture feature detection based on Gabor filter;

Design of optimized Gabor filter for multi-edges detection;

The parameter selection of Gabor filter for iris feature extraction;

Method for face description and recognition by local multi-channel Gabor filters and ICA;

A slub detection method based on Gabor filters

This paper designed a set of multi-scale、multi-directional real Gabor filters Incorporating into the human visual characteristics,the concept of mutual information entropy in rough set was introduced to evaluate the effect of the features extracted from different filters on clustering,get rid of the redundancy features and gave prominence to the features which had good distinguishing abilities.

Compared with Gabor filters, Log-Gabor filters can be constructed to have wider bandwidth with optimal spatial localization.

This paper analyzed the characteristics of graphics Gabor filters and calculated the parameters of Gabor filter banks commonly used.