Image segmentation application combining moving grid method and level set method
Hongjian Shi, Wan-lung Lee · Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021) · 2022
Intensity inhomogeneity is widely present in real images. When there is intensity inhomogeneity in the image, the curve evolution will be guided by the wrong target edge, which seriously affects the efficiency and accuracy of image segmentation. Aiming at the intensity inhomogeneity distribution in the medical image, this paper proposes an image segmentation algorithm that combines moving grid method and level set method. The grid is encrypted at the uneven intensity level to make the image uniform and applied to the image segmentation. By calculating a monitor function about image intensity gradient, this paper makes grid encryption automatically implemented with the change of image gradient. This makes it more accurate to calculate image segmentation at uneven intensity. In order to improve efficiency, this paper will reduce the grid to 1/4. Then the level set method is applied to achieve computational acceleration. The final results show that the model in this paper has high segmentation accuracy and efficiency for intensity inhomogeneity images.