Image Segmentation Method Based on Watershed Algorithm and Morphological Labeling

Abstract

The invention provides an image segmentation method based on the watershed algorithm and morphological markers, which performs median filtering on the grayscale image to obtain the filtered image; uses the OTSU Otsu method to obtain the binarized image on the filtered image; uses reconstruction-based The morphological operation processes the binarized image to obtain the feature-marked image; the watershed algorithm is used to transform the feature-marked image to obtain the segmented image. The image segmentation method provided by the present invention uses OTSU Otsu method and median filter to filter the impurities and noise points of the image, and as the preliminary mark source of the watershed algorithm, effectively eliminates the interference of noise; adopts the morphological operation method, in While ensuring that the information of the effective area is not lost, it can separate some fuzzy areas or connected areas to ensure the integrity and consistency of image segmentation; combined with the calculation of connected domains, it can eliminate non-noisy invalid targets and information, and accurately locate The labeling of the watershed algorithm eliminates the phenomenon of over-segmentation.

Description

Image Segmentation Method Based on Watershed Algorithm and Morphological Labeling technical field The invention relates to an image segmentation processing method, in particular to an image segmentation processing method based on a watershed algorithm and morphological markers, which can be used for various image segmentation including micro-nano particle distribution, cell or defect detection. Background technique Image segmentation is a very important step in image processing and detection analysis. It can divide the target image into several regions with certain similarity and consistency characteristics, accurately locate these regions and further analyze some of their characteristics. and processing. Image segmentation is usually used for further image analysis, detection, evaluation, etc. The accuracy of segmentation and the consistency of regions will directly affect the value of subsequent work. The mainstream image segmentation methods are generally divided into...

AI Technical Summary

Problems solved by technology

The image segmentation method provided by the invention can not only ensure the accuracy of marking, eliminate invalid information such as impurities and noise, but also effectively solve the problem of over-segmentation when the watershed algorithm is used to segment images

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