Abstract:

In order to improve the accuracy of garbage in the process of identification and classification, this paper proposed a method based on improved Canny algorithm for garbage image edge detection in the process of garbage image preprocessing. The method optimized the edge detection of garbage images from three aspects: traditional Canny algorithm filtering, gradient direction and threshold adaptive. For the poor performance of Gauss filter used by traditional Canny algorithm in limitation of removing gauss noise and loss of edge details, the improved gradient reciprocal weighting method was used to filter. For the problem that the Canny algorithm was easy to detect the false edge, the edge was refined by adding the direction gradient template in the process of calculating the gradient direction of the image. At the same time, the minimum error method was used to solve the limitation of manually setting the threshold, and the threshold could be adaptive. The experimental result showed that this method improved the denoising performance and obtained better edge detection effect, which provided technical support for the subsequent classification and classification of garbage images.

Key words: edge detection, Canny algorithm, gradient reciprocal weighted filtering, gradient direction, minimum error method, garbage image