Backed fabric image division method based on texture suppressing smoothing filtering and watershed algorithm

Abstract

The invention discloses a backed fabric image division method based on texture suppressing smoothing filtering and watershed algorithm. The backed fabric image division method based on the texture suppressing smoothing filtering and watershed algorithm includes that using a hybrid median filtering algorithm to filter and scan noise of features of a fabric image with backed weave based on color mode conversion; filtering through a texture suppressing smoothing filtering algorithm to remove the backed weave shadows and yarn textures with the same color from the fabric image and keep yarn color features; extracting the chromatic gradient of the fabric image, and performing image division through the watershed algorithm to obtain a regional mark image; combining the segmented regions with similar colors to obtain a color separation index image of the fabric image. By means of the backed fabric image division method based on the texture suppressing smoothing filtering and watershed algorithm, edges of different colors of yarns are effectively kept based on smoothing the yarn textures with the same color and backed weave edge shadows, and the problems that the edge details between regions are weakened after performing Gaussian filter, and the yarn textures are reserved as edges after performing bilateral filter are avoided.

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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