Обзорная статья

Techniques and Challenges of Image Segmentation: A Review

Ying YuDepartment of Electronic and Optical Engineering, Army Engineering University of PLA, Shijiazhuang 050003, ChinaChunping WangDepartment of Electronic and Optical Engineering, Army Engineering University of PLA, Shijiazhuang 050003, ChinaQiang FuDepartment of Electronic and Optical Engineering, Army Engineering University of PLA, Shijiazhuang 050003, ChinaRenke KouDepartment of Electronic and Optical Engineering, Army Engineering University of PLA, Shijiazhuang 050003, ChinaFuyu HuangDepartment of Electronic and Optical Engineering, Army Engineering University of PLA, Shijiazhuang 050003, ChinaBoxiong YangSchool of Information and Intelligent Engineering, University of Sanya, Sanya 572022, ChinaTingting YangSchool of Information and Intelligent Engineering, University of Sanya, Sanya 572022, ChinaMingliang GaoSchool of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China

2023en

ABI

Аннотация

Image segmentation, which has become a research hotspot in the field of image processing and computer vision, refers to the process of dividing an image into meaningful and non-overlapping regions, and it is an essential step in natural scene understanding. Despite decades of effort and many achievements, there are still challenges in feature extraction and model design. In this paper, we review the advancement in image segmentation methods systematically. According to the segmentation principles and image data characteristics, three important stages of image segmentation are mainly reviewed, which are classic segmentation, collaborative segmentation, and semantic segmentation based on deep learning. We elaborate on the main algorithms and key techniques in each stage, compare, and summarize the advantages and defects of different segmentation models, and discuss their applicability. Finally, we analyze the main challenges and development trends of image segmentation techniques.

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Идентификаторы

DOI: 10.3390/electronics12051199

Цитирования и источники

Цитирований: 3Использованных источников: 0

Показатели — AkademScholar