Recent advances on image edge detection: A comprehensive review

被引：68
|
作者：
Jing, Junfeng [1 ,2 ]
Liu, Shenjuan [1 ]
Wang, Gang [3 ]
Zhang, Weichuan [4 ]
Sun, Changming [5 ]
机构：
[1] Xian Polytech Univ, Coll Elect & Informat, Xian 710048, Peoples R China
[2] Xian Polytech Univ, Branch Shaanxi Artificial Intelligence Joint Lab, Xian, Peoples R China
[3] Beijing Inst Basic Med Sci, Beijing 100850, Peoples R China
[4] Griffith Univ, Inst Integrated & Intelligent Syst, Nathan, Qld, Australia
[5] CSIRO Data61, POB 76, Epping, NSW 1710, Australia
来源：
NEUROCOMPUTING | 2022年 / 503卷
基金：
中国国家自然科学基金;
关键词：
Edge detection; Hand-crafted; Machine learning; Evaluation criteria; Evaluation database; ANISOTROPIC DIFFUSION; FACE RECOGNITION; CORNER DETECTION; CONTOUR; ALGORITHM; COLOR; NOISE; OPTIMIZATION; SEGMENTATION; FRAMEWORK;
D O I：
10.1016/j.neucom.2022.06.083
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Edge detection is one of the most important and fundamental problems in the field of computer vision and image processing. Edge contours extracted from images are widely used as critical cues for various image understanding tasks such as image segmentation, object detection, image retrieval, and corner detection. The purpose of this paper is to review the latest developments on image edge detection. Firstly, the definition and properties of edges are introduced. Secondly, the existing edge detection methods are classified and introduced in detail. Thirdly, the existing widely used datasets and evaluation criteria for edge detection methods are summarized. Finally, future research directions for edge detection are elaborated. (C) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页码：259 / 271
页数：13
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