Canny optimisation of the dynamic image colour automatic segmentation algorithm

Abstract

Aiming at the current dynamic image colour automatic segmentation algorithm in image segmentation, there are problems of missing image edge information, poor clarity, large impact noise, and low-image segmentation accuracy. A Canny-optimised automatic colour segmentation algorithm for dynamic image is proposed. Noise in dynamic images is filtered by a switch-type median filter using a Laplacian operator test. Three primary colour features of the dynamic image edge were extracted by the compensation algorithm, and the edge dynamic image weighted fusion was completed based on the primary colour feature. The Canny operator is used to optimise the concave research method, analyse the dynamic image gradient amplitude histogram, select the adaptive double threshold value as the best threshold according to the image characteristics, and realise the automatic dynamic image colour segmentation based on the best segmentation threshold. The results show that the proposed algorithm has complete image edge information and good segmentation effect, and can effectively filter out impact noise and improve the accuracy of image segmentation.