Human face detection method and human face detection equipment

Abstract

The invention provides a human face detection method, comprising the steps of: importing: importing an image to be processed; sub-image extracting: traversing the image to be processed by using windows of different scales to extract parts of the image to be processed in the windows to serve as sub-images; preprocessing: specific to the sub-images, calculating a Sobel image of each sub-image by using a horizontal Sobel template, and excluding the sub-image if the ratio of the sum of Sobel response values of a predetermined region in the Sobel image to the total Sobel response value of the sub-image is smaller than a preset ratio threshold; detecting: specific to the sub-images passing the preprocessing, excluding non-human-face images by using an Adaboost cascade classifier to obtain candidate human-face sub-images; and verifying: specific to the candidate human-face sub-images, verifying the candidate human-face sub-images by using an Adaboost classifier established based on Haar-Sobel features so as to exclude the non-human-face sub-images, wherein the rest sub-images are taken as the human-face sub-images. The invention further provides human-face detection equipment correspondingly.

Description

technical field [0001] The invention relates to a face detection method and face detection equipment. Background technique [0002] With the development of computer technology, especially pattern recognition technology, face detection appears in people's field of vision as a technical direction. Face detection technology can be used as the basic work of various application projects in the field of image processing and video analysis, such as face recognition, face image retrieval, and driver fatigue detection. [0003] Among the peripheral technologies of the face detection technology, for example, Patent Document 1 (US 6415053B1) proposes a technology of calculating and storing gradient information representing directions. In this patent, many directional templates are used to improve the accuracy of edge region extraction. It should be pointed out that the purpose of this patent is to locate the edge area in the image, and it cannot be directly used for face detection. ...

AI Technical Summary

Problems solved by technology

The main limitation of the invention is that since the implementation of the patented technology relies on a color model which is not robust to lighting, its performance is severely limited

[0005] Although the design idea of ​​the traditional face detection method is to ensure the detection performance, detection speed and low false detection rate of the face detector at the same time, such a design idea makes the training process of the face detector difficult and complicated. In terms of performance, it is actually difficult to cover everything

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