A Segmentation Method of Heavy Fabric Image Based on Texture Suppression Smoothing Filter and Watershed Algorithm

Abstract

The invention discloses a heavy fabric image segmentation method based on texture suppression smoothing filtering and watershed algorithm. This method is based on the characteristics of fabric images with heavy tissue and uses a hybrid median filtering algorithm to filter out scans based on color mode conversion. Noise; then filter through the texture suppression smoothing filter algorithm to remove heavy tissue shadows and same-color yarn textures in the fabric image, retaining the yarn color characteristics; then extract the color difference gradient of the fabric image, perform image segmentation through the watershed algorithm, and obtain the region Mark the image; finally, merge the segmented areas with similar colors to obtain the color separation index image of the fabric image; while smoothing the yarn texture of the same color and reorganizing the edge shadows, it effectively maintains the edges of yarns of different colors, avoiding Problems include the weakening of edge details between regions after Gaussian filtering and the retention of yarn texture as edges by bilateral filtering.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a heavy fabric image segmentation method based on texture suppression smoothing filter and watershed algorithm. Background technique [0002] Image segmentation is the basis of fabric image processing and analysis, and the accuracy of segmentation often determines the effectiveness of post-processing such as fabric image structure extraction, content analysis, and retrieval. Backed weave is the interweaving of two or more sets of warp yarns with one set of weft yarns, or the interweaving of two or more sets of weft yarns with one set of warp yarns to form a double or more overlapping weave. Heavy-weight fabrics are made of yarns of different colors or different raw materials. As the number of overlapping groups of warp or weft yarns changes, the resulting fabric has rich colors and layers. The image of the heavy fabric is not an ideal planar structure, and the image obt...

AI Technical Summary

Problems solved by technology

For heavy fabric images, using edge detection for image segmentation first needs to convert the color image into a grayscale image, but due to the existence of color deviation, yarn texture and shadow, it is difficult to extract ideal continuous and closed edges, so image segmentation often Inaccurate

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