Multi-view image adaptive enhancement method for conveyor belt fault detection

The images collected to detect the fault of conveyor belt have some problems of non-uniform illumination, and poor image quality.It makes fault detection and recognition become difficult.In order to improve the accuracy of fault detection of mine conveyor belt, a method for adaptive enhancement of multi-view images has been proposed in this paper.Firstly, a multi-scale Retinex method with scale adaptive is used to extract the illumination components of an image.According to the extracted illumination component, the non-uniform illumination correction of multi-view images is achieved by using the adaptive gamma function.Finally, the image contrast is enhanced.The experimental results show that this method has many effects, such as removing the effect of non-uniform illumination and coal mine harsh environments, making the average intensity of the image collected by the linear array camera under different viewpoints and illumination conditions consistent, compressing the image dynamic range, improving the image contrast, making the detail of dark area more obvious in the image.This method contributes to improve the accuracy of fault detection, and is suitable for the on-line fault detection of mine conveyor belts.