Superpixel segmentation based on image density

被引：3

作者：

Qiu, Dong-Fang ^{[1
]}

Yang, Hua ^{[1
]}

Deng, Xue-Feng ^{[1
]}

Liu, Yan-Hong ^{[1
]}

机构：

[1] Shanxi Agr Univ, Coll Informat Sci & Engn, Taigu, Shanxi, Peoples R China

来源：

SYSTEMS SCIENCE & CONTROL ENGINEERING | 2023年 / 11卷 / 01期

关键词：

Image density; clustering; superpixel; image segmentation;

D O I：

10.1080/21642583.2023.2185915

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Superpixel segmentation can get the middle features in image processing, effectively reduce the dimensionality of the image, and is widely used in image processing fields. To get the regular and compact superpixels in real-time, a superpixel segmentation algorithm based on image density is proposed in this paper. Firstly, the image is uniformly divided according to the number of superpixels to be obtained. Secondly, to get the clustering ability of the pixels, the density image is produced. Thirdly, the seed is chosen in each sub-region block according to the density and then the superpixels are obtained by clustering. During the clustering process, the pixel around the seed should be added into the superpixel if it meets the conditions, and the small supeipixels are merged into the big superpixels around them. Finally, the result shows that the proposed algorithm has the best segmentation effect, and a good balance in accuracy, regularity, and time cost.

引用

页数：7

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