A method and device for reducing storage capacity of face detection

Abstract

The invention relates to method and equipment for reducing the storage capacity in human face detection. The method comprises the following steps of: reducing pixel bit width of an image to be detected; diffusing the error of a gray value of each pixel point, which is generated in the process of reducing the pixel bit width, to adjacent pixel points by adopting an error diffusion method; solving an integral image and an integrated square image of the image subjected to the pixel bit width reduction and the error diffusion, wherein the storage capacity required by the integral image is (the pixel bit width plus logarithm2(W*H))*W*H bit; the storage capacity required by the integrated square image is (the pixel bit width*2+logarithm2(W*H))*W)*H bit; W is the pixel quantity of the image width; and H is the pixel quantity of image height. According to the method and equipment, the pixel bit width of the image is reduced and the error diffusion is carried out; and on the premise of no influence on a human face detection algorithm, the storage spaces required by the integral image and the integrated square image in a hardware chip are reduced and the cost of the chip is reduced.

Description

technical field [0001] The invention relates to a method and equipment for reducing the storage capacity of human face detection. Background technique [0002] With the popularization of video surveillance, face detection technology becomes more and more important. Among various face detection technologies, the face detection technology using AdaBoost adaptive enhancement algorithm has a higher accuracy rate and has been implemented by hardware chips. This technology generally uses an 8-bit wide grayscale image output by a CCD or CMOS camera as input. [0003] figure 1 It is an example diagram of the micro-features used in the face detection technology based on the AdaBoost adaptive enhancement algorithm. [0004] Such as figure 1 As shown in Fig. 1, this technique employs many typical micro-features during the face detection process of this technique. [0005] For example, the leftmost microfeature represents a type of template. In the processing, it is necessary to f...

AI Technical Summary

Problems solved by technology

[0012] It can be seen from the above formula that the storage capacity required by the integral image and the square integral image has a direct relationship with the pixel bit width. If the pixel bit width is too high, the storage capacity required by the integral image and the square integral image will be large, thus Increase the cost of hardware chips

Images