Author:
Cai Zhaoquan,Liang Yihui,Huang Han
Funder
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province (CN)
the Fundamental Research Funds for the Central Universities, SCUT
Science and Technology Planning Project of Guangdong Province
Science and Technology Planning Project of Huizhou City
Guangdong Higher Education Discipline and Profession Special Fund Projects
Guangdong ”Twelfth Five-Year Plan” Education Information Technology Research Projects
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Reference20 articles.
1. Arbelaez P, Maire M, Fowlkes C, Malik J (2011) Contour detection and hierarchical image segmentation. IEEE Trans Pattern Anal Mach Intell 33(5):898–916
2. Borsotti M, Campadelli P, Schettini R (1998) Quantitative evaluation of color image segmentation results. Pattern Recogn Lett 19(8):741–747
3. Carreira J, Sminchisescu C (2012) Cpmc: automatic object segmentation using constrained parametric min-cuts. IEEE Trans Pattern Anal Mach Intell 34(7):1312–1328
4. Chabrier S, Emile B, Rosenberger C, Laurent H (2006) Unsupervised performance evaluation of image segmentation. EURASIP Journal on Applied Signal Processing 2006:217–217
5. Chen HC, Wang SJ (2004) The use of visible color difference in the quantitative evaluation of color image segmentation. In: IEEE international conference on acoustics, speech, and signal processing, 2004. Proceedings (ICASSP’04), vol 3. IEEE, pp iii–593
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Quality Evaluation of Image Segmentation in Mobile Augmented Reality;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024
2. Metric Learning with Feature Embedding for Segmentation Quality Evaluation;2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE);2021-11-26
3. Image segmentation evaluation: a survey of methods;Artificial Intelligence Review;2020-04-18