DocumentCode :
2486755
Title :
A Force Field Driven SOM for boundary detection
Author :
He, Yu ; Xu, Songhua ; Miranker, Willard L.
Author_Institution :
Dept. of Comput. Sci., Yale Univ., New Haven, CT, USA
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
7
Abstract :
We will introduce a method to extract object boundaries from an image. This method utilizes a deformable curve based on the Self Organizing Map algorithm. The proposed SOM has some unique properties such as batch update and neuron insertion/deletion. These properties can make the SOM converge to object concavities as well as maintain a uniform distribution of neurons along the SOM. In comparison with other traditional active contour methods, this algorithm is less sensitive to initialization more flexible in noisy conditions. It outperforms the Gradient Vector Flow method.
Keywords :
curve fitting; feature extraction; object detection; self-organising feature maps; boundary detection; deformable curve; force field driven SOM; object boundary extractioni; object concavities; self organizing map algorithm; Active contours; Computational modeling; Deformable models; Force; Image edge detection; Kernel; Neurons; Active Contour; Edge Detection; Self Organizing Map;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
ISSN :
1098-7576
Print_ISBN :
978-1-4244-6916-1
Type :
conf
DOI :
10.1109/IJCNN.2010.5596310
Filename :
5596310
Link To Document :
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