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http://dx.doi.org/10.5351/KJAS.2009.22.3.569

Edge Detection using Morphological Amoebas Noisy Images  

Lee, Won-Yeol (Korea Science Academy)
Kim, Se-Yun (Korea Science Academy)
Kim, Young-Woo (Korea Science Academy)
Lim, Jae-Young (Korea Science Academy)
Lim, Dong-Hoon (Department of Information Statistics, Gyeongsang National University)
Publication Information
The Korean Journal of Applied Statistics / v.22, no.3, 2009 , pp. 569-584 More about this Journal
Abstract
Edge detection in images has been widely used in image processing system and computer vision. Morphological edge detection has used structuring elements with fixed shapes. This paper presents morphological operators with non-fixed shape kernels, or amoebas, which take into account the image contour variations to adapt their shape. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with PFOM and ROC curves. The Experiments demonstrate that these novel operators outperform classical morphological operations with a fixed, space-invariant structuring elements for edge detection applications.
Keywords
Noisy images; mathematical morphology; amoeba; edge detection; structuring element;
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