Unsupervised segmentation evaluation: an edge-based method

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

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