Leather Image Segmentation Based on Proportional Templateand Boundary Adjustment
基于比例模板和边界校正的皮革图像分割

Using leather's texture character to performance intelligent segmentation is an efficient way to improve leather product efficiency and production quality. A new method for leather image segmentation is proposed based on proportional template and region boundary adjustment. First, according to the previous experience of leather segmentation, a proportional template used to performance leather image's coarse segmentation is built, then, the leather image is divided into several coarse regions. Second, pixel on the boundary is selected as the center to design a window, and the mean texture period inside the window is computerized using auto-correlation function distribution. By the same way, the mean texture period of the window belong to the region center is also calculated. Two mean texture period are compared to distinguish whether the location of pixel on the boundary need to adjust. The above processes are repeated until the region's texture consistency is limited to scheduled error scope. Simulations show that the proposed method is simple and efficient to segment leather image.