A novel improved SLIC superpixel segmentation algorithm

Chen, Zhijie; Zhong, Zhaoqi; Pan, Xiangyu; Xi, Xin

doi:10.1109/iccasit55263.2022.9987217

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2023

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“…The clustering and segmentation method of an image is mainly to cluster the pixels with similar values together, and finally divides all the pixels into different categories through iterative clustering results. The more popular ones are K-Means [13] and SLIC [14] superpixel separation algorithms. The image segmentation method implemented by using graph theory subtly transforms the segmentation problem into the task of dividing the graph.…”

Section: Related Workmentioning

confidence: 99%

Non-interactive GrabCut image segmentation method

Wang,

Zeng

et al. 2023

Third International Conference on Image Processing and Intelligent Control (IPIC 2023)

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The GrabCut image segmentation algorithm based on the principle of graph theory has been extensively used in the field of computer vision. However, the shortcoming is that it requires human-computer interaction to complete the ROI region selection to solve the segmentation task of the foreground image. Therefore, it cannot meet the requirements of fully intelligent image processing. In order to eliminate human-computer interaction and realize smart region selection, this paper proposes a ROI smart region generating and fine-tuning method to improve the GrabCut method, so as to realize intelligent image segmentation. The experimental results show that our method is compatible with both single-target and multi-target foreground image segmentation solutions.

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Section: Related Workmentioning

confidence: 99%