Real-time face optimal selection method based on video sequence

Abstract

The invention discloses a real-time face optimal selection method based on a video sequence. The method comprises the following steps: a face image is acquired; face clarity, face size and opening degree of human eyes act as three indexes for face quality evaluation so that a face integrated evaluation score ImageScore is calculated; the ImageScore of the first frame of the face image is assigned to an initial face optimal image MaxScore and the face image is stored; the MaxScore after assignment is compared with the ImageScore of other frames of the face image, and the face image corresponding to the higher ImageScore is stored and the ImageScore is assigned to the MaxScore again; and the MaxScore value is cyclically updated and the stored optimal face image is updated until the image sequence with the face cannot be acquired, and the cycle is ended and the image corresponding to the stored MaxScore is the optimal face image. The face image with higher quality can be screened for identification via comparison of the integrated evaluation indexes of face quality in the video sequence under the situation of not knowing the face sequence image in advance; besides, the calculation method is simple with real-time performance.

Description

technical field [0001] The invention relates to an image quality evaluation method, in particular to a real-time face selection method based on video sequences. Background technique [0002] With the development of computer vision technology, face recognition technology has been widely used in many electronic systems, such as access control systems, bayonet systems, electronic passports, public security, bank self-service systems, information security, etc. However, in the process of face recognition, misidentification is easy to occur, so how to improve the recognition rate is particularly important. Using a high-quality face image for recognition will produce a higher matching rate, thereby improving the face recognition rate. [0003] In order to select a face image with better quality from the sequence images, it is necessary to evaluate the quality of the face image and select the face image with the highest score. The current image quality evaluation methods are main...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem of high cost and long period of subjective evaluation method, and the current objective evaluation method has the problem of complicated calculation method, the present invention adopts objective evaluation method to provide a real-time face selection method based on video sequence

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