Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (1): 213-218.

### Target Segmentation Algorithm Based on SLIC and Region Growing

HAN Jipu, DUAN Xianhua, CHANG Zhen

1. School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212000,  China
• Online:2021-01-01 Published:2020-12-31

### 基于SLIC和区域生长的目标分割算法

1. 江苏科技大学 计算机学院，江苏 镇江 212000

Abstract:

The segmentation result of the traditional region growing algorithm depends on the selection of the seed point. The noise of the image and the uneven grayscale value are easy to form the segmentation cavity in the process of segmentation. Aiming at the above problems, an improved region growing algorithm based on superpixel is proposed. Frist of all, the Laplacian sharpening is used to enhance the boundary of the target to be segmented. According to the features of gray similarity, the SLIC（Simple Linear Iterative Clustering） superpixel segmentation method is used to segment the original image into several irregular regions. Then an undirected weighted graph based on irregular regions will be established. A region is selected as a seed, the region is grown in units of the segmented irregular regions according to the undirected weighting map. To clarify the edge area, the region growing algorithm in pixels runs at the edge of the segmentation target finally. Compared with the traditional region growing algorithm, the improved algorithm is less affected by the seed point selection in the segmentation result, and the improved algorithm can effectively solve the problem of segmentation holes. Compared with clustering segmentation, Otsu threshold segmentation method, the proposed algorithm has obvious advantages in segmentation accuracy.