Superpixel segmentation based on image density
| Autor: | Dong-Fang Qiu, Hua Yang, Xue-Feng Deng, Yan-Hong Liu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Systems Science & Control Engineering, Vol 11, Iss 1 (2023) |
| Druh dokumentu: | article |
| ISSN: | 21642583 2164-2583 |
| DOI: | 10.1080/21642583.2023.2185915 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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