DocumentCode :
3624646
Title :
Improvements in Image Segmentation by Applying Hopfield Neural Networks
Author :
Marija Uscumlic;Irini Reljin;Dragi Dujkovic;Branimir Reljin
Author_Institution :
Faculty of Electrical Engineering, University of Belgrade, Bulevar Kralja Aleksandra 73, 11000 Belgrade, Serbia, E-mail: milanu@beotel.yu
fYear :
2006
Firstpage :
37
Lastpage :
40
Abstract :
Hundreds of algorithms for different aspects of image segmentation have been developed. In this paper goals of using segmentation in video and multimedia systems are considered. Thus direction of improvements is towards forming masks and matte signals. The idea is to spread locally dominant segment in already segmented image. This problem is set as optimization problem and solution can be achieved by Hopfield neural network. Presented results are obtained applied to color detected segmentation, performed by mean shift algorithm
Keywords :
"Image segmentation","Hopfield neural networks","Shape","Neural networks","Color","Motion detection","Seminars","Videoconference","Multimedia systems","Image edge detection"
Publisher :
ieee
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2006. NEUREL 2006. 8th Seminar on
Print_ISBN :
1-4244-0432-0
Type :
conf
DOI :
10.1109/NEUREL.2006.341170
Filename :
4147158
Link To Document :
بازگشت