GSA-based concave image segmentation method

Abstract

The invention discloses a GSA-based concave image segmentation method. Firstly grayscale processing is performed on an original image, then initial snake element convergence is completed by using a GSA model, and the final snake element convergence is finally completed through a greedy algorithm. According to the method, normalization processing is performed on the image, the continuous force, the bending force and the image fore are balanced, and fitting of the snake elements to the position around the target contour, especially fitting to the concave area of the image, is rapidly and uniformly performed under the premise of guaranteeing the original sequence of the snake elements so that the efficient computing advantage of the GSA model can be maintained, the contour extraction accuracy can be enhanced, and especially the problem of concave target contour extraction can be greatly processed by the method.

Description

technical field [0001] The invention relates to a concave image segmentation method based on GSA Background technique [0002] In the research of computer vision, traditional object detection is mainly through image segmentation and edge detection through a bottom-up process. This process takes less account of the characteristics of the target itself, so it is not effective enough. The snake model, also known as the active contour model, was first proposed by Kass et al. This method has been widely used in image segmentation, detection, recognition and other fields. Different from traditional image segmentation methods, the Snake model makes full use of the characteristics of the target image itself, combining information such as the size, position, and shape of the image with features such as grayscale and gradient of the image. At present, the Snake model has become the most commonly used method for image target detection. [0003] There are some problems in the traditi...

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Problems solved by technology

[0005] The technical problem to be solved by the present invention is: Aiming at the problem of low computational efficiency of the Snake model and unsatisfactory processing of concave images, a GSA-based concave image segmentation method is designed. Force, bending force and image force, under the premise of ensuring the original sequence of the snake element, allow the snake element to quickly and evenly fit around the target contour, especially fit into the concave area of ​​the image

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