A new filtering algorithm for video monitoring image of coal mine

Abstract

In view of problems of high noise intensity and low contrast of video monitoring image of coal mine, a new filtering algorithm for video monitoring image of coal mine was proposed. Firstly, edge of image is detected by use of self-adaptive Canny operator, so as to realize effective separation of edge image and non-edge image. Then histogram equalization algorithm is introduced to process the edge image, so as to highlight edge information and improve contrast of the image. Meanwhile, classical mathematical morphology filtering algorithm is improved through construction of filter and design of structural element, and it is applied to filtering of the non-edge image. Finally, image fusion mechanism is introduced to realize weight fusion of the processed edge image and non-edge image. The experimental results show that the algorithm has better filtering effect than wavelet threshold algorithm and classical mathematical morphology filtering algorithm.

Keywords

• video monitoring image
• edge detection
• image segmentation
• canny operator
• mathematical morphology filtering
• histogram equalizatio