A 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 space transformation, which mainly solves the inability of the traditional face recognition method due to the fact that the intra-class scatter matrix is ​​zero under the condition of only a single training sample image. application problem. This method uses Gabor wavelet to extract the spatial feature vector from the original single-sample image, then fuses the extracted spatial feature vector and the original spectral feature vector, uses the feature space transformation method to perform low-dimensional feature space transformation on the fusion feature matrix, and converts it to Transform into a low-dimensional subspace, and finally, use the nearest neighbor classifier to complete the identification. The method of the invention can accurately complete the recognition of a single-sample human face, improves the recognition precision and reduces the calculation cost. Compared with the prior art, the face recognition method proposed by the present invention is more effective and robust.

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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