DocumentCode :
2923745
Title :
Improving the Graph-Based Image Segmentation Method
Author :
Zhang, Ming ; Alhajj, Reda
Author_Institution :
Dept. of Comput. Sci., Calgary Univ., Alta.
fYear :
2006
fDate :
Nov. 2006
Firstpage :
617
Lastpage :
624
Abstract :
Sensor devices are widely used for monitoring purposes. Image mining techniques are commonly employed to extract useful knowledge from the image sequences taken by sensor devices. Image segmentation is the first step of image mining. Due to the limited resources of the sensor devices, we need time and space efficient methods of image segmentation. In this paper, we propose an improvement to the graph-based image segmentation method already described in the literature and considered as the most effective method with satisfactory segmentation results. This is the preprocessing step of our online image mining approach. We contribute to the method by re-defining the internal difference used to define the property of the components and the threshold function, which is the key element to determine the size of the components. The conducted experiments demonstrate the efficiency and effectiveness of the adjusted method
Keywords :
data mining; graph theory; image segmentation; graph-based image segmentation; image mining; knowledge extraction; sensor devices; Computer science; Data mining; Image analysis; Image segmentation; Image sensors; Image sequences; Merging; Monitoring; Pixel; Size control; image mining; image segmentation; sensor devices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, 2006. ICTAI '06. 18th IEEE International Conference on
Conference_Location :
Arlington, VA
ISSN :
1082-3409
Print_ISBN :
0-7695-2728-0
Type :
conf
DOI :
10.1109/ICTAI.2006.66
Filename :
4031952
Link To Document :
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