Mixed-region-based moving contour model image segmentation method

Abstract

The invention discloses a mixed-region-based moving contour model image segmentation method. The method comprises: enhancement processing is carried out on an original image based on an image enhancement algorithm; a mixed-region-based moving contour model energy functional is built by using a local gray scale fitting item of the original image and a global gray scale fitting item of an enhanced image; and then the constructed energy functional is solved by a variational method, mathematical calculation is carried out by using solution framework of a variational level set and a contour curve is expressed in a hidden level set manner, the constructed energy functional is transformed into a partial differential equation by using a gradient descending flow and an Euler-Lagrangian equation, an optimal solution of the partial differential equation is obtained based on an iterative approximation method, and then a final target boundary contour is obtained. The method is not sensitive to the position of the initial contour curve and gray scale nonuniformity of the image; the segmentation efficiency and precision are high; and the influence of noises is low; and the robustness of the segmentation result is high.

Description

technical field [0001] The invention relates to an image segmentation method in the field of image processing, in particular to an active contour model image segmentation method based on a mixed region. [0002] technical background [0003] Most of the information obtained by the human brain from the outside world is obtained through the eyes. The light emitted or reflected by objects or scenes is refracted to the retina through the lens in the eye, forming an inverted image on the retina. Then it is transmitted to the brain by the visual perception nerve, and the image of the object or scene can be seen after the brain processes it, and the image contains rich description information of the object or scene it expresses, so the image information is the key to obtain information in human daily life main method. [0004] With the rapid development of science and technology, especially the development of imaging technology, computer technology and signal processing theory, peo...

AI Technical Summary

Problems solved by technology

In the geometric active contour model, the model using the global gray level information of the image will be sensitive to the gray level inhomogeneity of the image; the model using the local gray level information of the image will be sensitive to the initial contour position; and the model combining the global and local gray level information of the image There will be a problem with setting the weight coefficient of the global item

Images