Face recognition method under low resolution condition

Abstract

The invention discloses a face recognition method under a low resolution condition. M low-resolution facial image samples and a to-be-recognized facial image are normalized to a preset size, sliding block LBP feature vectors are respectively extracted, and an extraction method comprises the following steps: getting LBP vector images of the facial images, obtaining an LBP histogram feature vector of each sliding block area by adopting sliding block transverse and statistics, arranging the LBP histogram feature vectors according to serial numbers of the sliding block areas, and obtaining the sliding block LBP feature vectors of the facial images; and the sliding block LBP feature vectors of the M facial image samples and the sliding block LBP feature vector of the to-be-recognized facial image are constructed into a matrix, then dimensionality reduction processing is performed, and recognition is performed according to the feature vectors in a feature matrix after dimensionality reduction. The face recognition method disclosed by the invention can fully extract features of low-resolution facial images, and face recognition accuracy rate under the low resolution condition is improved.

Description

technical field [0001] The invention belongs to the technical field of face recognition, and more specifically relates to a face recognition method under low-resolution conditions. Background technique [0002] Face recognition is a kind of biometric technology. By comparing the collected face images with the images in the database, the identity of the person being collected is determined. It is natural, non-invasive, stable and individual differences. It has been widely used in daily life. With the increasing number of application scenarios, more and more small-sized and low-quality face images appear. These face images bring new problems and challenges to the face recognition system, that is, the accuracy of face recognition classification is obvious. decline. The problem of face image recognition with small size and low quality is generally referred to as low-resolution face recognition. [0003] Similar to traditional high-resolution face recognition systems, low-reso...

AI Technical Summary

Problems solved by technology

However, all of these algorithms have certain limitations for fully solving the low-resolution face recognition problem, such as the inconsistency between super-resolution enhancement and recognition targets, and limitations in the ability to express robust features at resolution, etc.

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