Application of image segmentation based on the artificial bee colony algorithm in fire detection of mine belt conveyor

The traditional method of mine belt conveyor fire accident detection is limited. A novel image processing method is proposed in this paper, which combines 2D-Dimensional Otsu, Canny dge detection and Artificial Bee Colony algorithm. The noise interference of image is reduced by using median filtering techniques. In order to obtain gray value and neighborhood gray scale average, 2-Dimensional histogram of image is constructed. The fitness function of Artificial Bee Colony algorithm is designed by 2-Dimensional Otsu method and the maximum value of the fitness function is the optimal threshold for image segmentation. Finally, the canny edge detection and grayscale morphology were used to extract the target. Theoretical analysis and simulation results show that the proposed method is effective to detect fire accident of mine belt conveyor in complex undeground environment.