DocumentCode
2170342
Title
Binary Morphological Model in Refining Local Fitting Active Contour in Segmenting Weak/Missing Edges
Author
Kamaruddin, Norhaslinda ; Jalab, H.A. ; Zainuddin, R. ; Abdullah, N.A.
Author_Institution
Dept. of Comput. Syst. & Technol., Univ. Malaya, Kuala Lumpur, Malaysia
fYear
2012
fDate
26-28 Nov. 2012
Firstpage
446
Lastpage
451
Abstract
Medical images are known to have poor quality which leads to difficulty in vision and segmentation process. Mainly, noise and intensity in homogeneity are two main characteristics that lead to gaps (missing at edges) at the boundary of the desired object. This paper investigated method that managed to smooth the image texture in order to overcome the gaps problem. Our method adopts the morphological closing operations using the diamond-shape structuring elements to overcome the above-mentioned problem. We applied the dilation and erosion operation to expand and later smooth the regions with gaps. Our method shows satisfaction results when dealing with binary image rather than working with gradient. The results obtained shows better accuracy as the evolving curve is following the pixels value in the binary image. The method proposed is executed based on the output from Local binary fitting energy.
Keywords
computer vision; edge detection; image segmentation; image texture; medical image processing; above-mentioned problem; binary image; binary morphological model; diamond-shape structuring element; dilation; erosion operation; image texture; local binary fitting energy; local fitting active contour refining; medical image; missing edge segmentation; morphological closing operation; segmentation process; vision process; weak edge segmentation; Local binary fitting energy; active contour model; medical image segmentation; morphological operations;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computer Science Applications and Technologies (ACSAT), 2012 International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4673-5832-3
Type
conf
DOI
10.1109/ACSAT.2012.60
Filename
6516395
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