Cotton foreign fiber image online dividing method and cotton foreign fiber image online dividing system

Abstract

The invention provides a cotton foreign fiber image online dividing method and a cotton foreign fiber image online dividing system. The cotton foreign fiber image online dividing method includes the following steps: S1, receiving cotton foreign fiber images, converting the cotton foreign fiber images to gray-level images and negating the gray-level images; S2, processing the negated gray-level images in blocks and judging whether to further process the gray-level images in refining mode; S3, reading image blocks needing refining processing, obtaining revised background gray-level images, leading the background gray-level images to subtract the original gray-level image blocks to obtain image blocks with backgrounds removed, and cutting the images in an OTSU method; and S4, performing expansive operation on the image blocks, comparing corresponding edge pixels of adjacent image blocks, and performing image linking on cracked foreign fiber target images in multiple images or image blocks based on overlap ratio of the corresponding edge pixels. The cotton foreign fiber image online dividing method and the cotton foreign fiber image online dividing system can effectively improve imagecutting speed and ensure cutting quality of the images.

Description

technical field [0001] The invention relates to an image processing system, in particular to a method and system for online processing of cotton foreign fiber images. Background technique [0002] my country is a big cotton production and consumption country, and a big exporter of cotton textiles. However, in the raw cotton processing process, a variety of foreign fibers are usually mixed in due to many reasons. Foreign fibers refer to non-cotton fibers and colored fibers that are mixed into cotton and have a serious impact on the quality of cotton and its products, such as chemical fibers, hair, silk, hemp, plastic film, plastic rope, dyed thread (rope, cloth), etc. , commonly known as "three wires". [0003] Although the content of foreign fibers in lint is small, it has a serious impact on the quality of textiles. Foreign fibers mixed into raw cotton are easily broken into scattered single fibers, which are difficult to remove in textile processing. During spinning, sc...

AI Technical Summary

Problems solved by technology

However, the threshold value obtained by this algorithm is only when the target image area is larger than 25% of the entire image, and the segmentation performance is close to optimal; when the moving target image area becomes smaller, the algorithm performance drops rapidly, resulting in the smaller the target image, the greater the threshold deviation value

On the other hand, the OTSU method also has a big problem in the image segmentation processing of the uneven background or the small difference between the gray level of the target image and the background gray level, and cannot obtain high-quality segmented images.

However, the cotton foreign fiber image is just a small target image, and there is a small difference between the gray level of the target image and the background gray level and the uneven gray level of the background image.

In the image segmentation process, if the OTSU rule is directly used, there will be serious over-segmentation.

On the other hand, when the image is segmented, it is not necessary to segment the background image that occupies most of the non-target image, and the unified segmentation process greatly increases the amount of meaningless calculations, which seriously reduces the use of the OTSU method. The segmentation speed caused a great waste of resources

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