An Overview of Contour Detection Approaches
文献类型:期刊论文
作者 | Xin-Yi Gong2,3![]() ![]() ![]() ![]() ![]() ![]() |
刊名 | International Journal of Automation and Computing
![]() |
出版日期 | 2018 |
卷号 | 15期号:6页码:656-672 |
关键词 | Contour detection contour salience gestalt principle contour grouping active contour. |
ISSN号 | 1476-8186 |
DOI | 10.1007/s11633-018-1117-z |
英文摘要 | Object contour plays an important role in fields such as semantic segmentation and image classification. However, the extraction of contour is a difficult task, especially when the contour is incomplete or unclosed. In this paper, the existing contour detection approaches are reviewed and roughly divided into three categories: pixel-based, edge-based, and region-based. In addition, since the traditional contour detection approaches have achieved a high degree of sophistication, the deep convolutional neural networks (DCNNs) have good performance in image recognition, therefore, the DCNNs based contour detection approaches are also covered in this paper. Moreover, the future development of contour detection is analyzed and predicted. |
源URL | [http://ir.ia.ac.cn/handle/173211/42442] ![]() |
专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
作者单位 | 1.Tianjin Intelligent Technology Institute of Institute of Automation, Chinese Academy of Science Co., Ltd, Tianjin 300300, China 2.University of Chinese Academy of Science, Beijing 100049, China 3.Research Center of Precision Sensing and Control, Institute of Automation, Chinese Academy of Science, Beijing 100190, China |
推荐引用方式 GB/T 7714 | Xin-Yi Gong,Hu Su,De Xu,et al. An Overview of Contour Detection Approaches[J]. International Journal of Automation and Computing,2018,15(6):656-672. |
APA | Xin-Yi Gong,Hu Su,De Xu,Zheng-Tao Zhang,Fei Shen,&Hua-Bin Yang.(2018).An Overview of Contour Detection Approaches.International Journal of Automation and Computing,15(6),656-672. |
MLA | Xin-Yi Gong,et al."An Overview of Contour Detection Approaches".International Journal of Automation and Computing 15.6(2018):656-672. |
入库方式: OAI收割
来源:自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。