In view of the fact that the size and distribution of sinter in production cannot be obtained directly and the accuracy and timeliness of manual detection are not high a sinter particle size identification method based on image enhancement and Hough transform is proposed. Firstly morphological open operation image pixel segmentation and Laplacian image sharpening operator are used for image enhancement. Then Gaussian filtering and image edge detection algorithm are applied. Finally Hoff circle detection algorithm is used for sinter particle size detection. The acquired images are processed in real time and the sinter particle size and distribution are detected. This method can quickly detect the sinter in the image and the image pixel segmentation method is based on the segmentation function of sinter and background pixel values which greatly reduces the noise in the image and improves the contrast and brightness of sinter and background and has high accuracy and timeliness of detection. This method overcomes the shortcoming of manual detection with an accuracy of up to 98%. The experiment shows that this method has positive effect on improving sinter production efficiency improving resource utilization rate and reducing personnel cost.