Single-sample face recognition method based on Gabor feature extraction and spatial transformation

Abstract

The invention discloses a single-sample face recognition method based on Gabor feature extraction and spatial transformation, and mainly solves the problem that a traditional face recognition method can not be applied since a within class scatter matrix is zero under a condition that only single training sample image is in the presence. The method comprises the following steps that: adopting a Gabor wavelet to extract a spatial feature vector from an original single sample image; then, carrying out fusion on the extracted spatial feature vector with an original spectral feature vector, utilizing a feature spatial transformation method to carry out low-dimension feature space transformation on a fused feature matrix, and transforming the fused feature matrix to a low-dimension subspace; and finally, utilizing a nearest neighbor classifier to finish recognition. By use of the method, single-sample face recognition can be accurately finished, recognition accuracy is improved, and calculation cost is lowered. Compared with the prior art, the face recognition method which is put forward by the invention exhibits better effectiveness and robustness.

Description

technical field [0001] The invention belongs to the field of pattern recognition and image processing, and relates to the face recognition problem under the situation that the traditional face recognition method cannot be used for a single face image because the scatter matrix in the class is zero; specifically, it is a Gabor feature-based The single-sample face recognition method of extraction and spatial transformation can be used for video surveillance and identity recognition in single-sample situations. Background technique [0002] Face recognition technology is the most important type of biometric recognition technology. It is currently widely used in video surveillance, supervision and law enforcement, multimedia, process control, identification and other fields. So far, many researchers have achieved a lot of scientific research results in this area. However, for harsh or specific environments, it often poses a new challenge to the face recognition system. For exam...

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Problems solved by technology

[0006] In view of the above-mentioned problems, the present invention proposes a single-sample face recognition method based on Gabor feature extraction and spatial transformation to solve the problem that the intra-class scatter matrix is ​​zero under the single-sample image scenario. Due to the feature dimension of face recognition, it can also guarantee a certain recognition performance

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