DocumentCode
2955258
Title
A contour based image segmentation algorithm using morphological edge detection
Author
Hsiao, Ying-Tung ; Chuang, Cheng-Long ; Jiang, Joe-Air ; Chien, Cheng-Chih
Author_Institution
Dept. of Electr. Eng., Tamkang Univ., Taipei, Taiwan
Volume
3
fYear
2005
fDate
10-12 Oct. 2005
Firstpage
2962
Abstract
In this paper, a novel approach for edge-based image segmentation is proposed. Image segmentation and object extraction play an important role in supporting content-based image coding, indexing, and retrieval. However, it´s always a tough task to partition an object in a graph-based image. We proposed an image segmentation algorithm by integrating mathematical morphological edge detector with region growing technique. The images are first enhanced by morphological closing operations, and then detect the edge of the image by morphological dilation residue edge detector. Moreover, we deploy growing seeds into the edge image that obtained by the edge detection procedure. By cross comparing the growing result and the detected edges, the partition lines of the image are generated. In this paper, we presented the theoretical backgrounds and procedure illustrations of the proposed algorithm. Furthermore, the proposed algorithm is implemented in C++ language and evaluate on several images with promising results.
Keywords
edge detection; feature extraction; image segmentation; mathematical morphology; C++ language; contour based image segmentation algorithm; graph-based image; morphological edge detection; object extraction; Boundary conditions; Computer vision; Detectors; Image coding; Image edge detection; Image segmentation; Morphological operations; Morphology; Partitioning algorithms; Video coding; Mathematical morphology; contour features; image segmentation; region growing; thin edge detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 2005 IEEE International Conference on
Print_ISBN
0-7803-9298-1
Type
conf
DOI
10.1109/ICSMC.2005.1571600
Filename
1571600
Link To Document