An intelligent computer method for automatic mosaic of sequential slub yarn images based on image processing

Abstract

In order to analyze the parameters of slub yarn from sequential images accurately, an automatic image mosaic method is proposed in this paper. In this method, a series of overlapping yarn images, which are captured from a moving slub yarn, are stitched into a panorama automatically. Background subtraction, image segmentation and judgment template traversal methods are applied to preprocess the sequential images for obtaining a test image. Subsequently, certain rows in the bottom of the test image are used as a template image to match the next image. The matching coefficient matrix is calculated between the template image and next image based on the normalized cross-correlation method. In the matrix, the coordinates of the peak value are found as the optimal matching points. Two kinds of slub yarn images captured under 40 fps are stitched by using the proposed method and the manual method, respectively. Finally, an objective method is formulated to evaluate the qualities of the image mosaic by the proposed method. The experimental results show that the proposed method can find the match position accurately and is highly consistent with the manual method.

Keywords

sequential yarn image image mosaic image processing slub yarn parameters normalized cross-correlation method

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