Title :
Automatic multilevel thresholding for image segmentation by the growing time adaptive self-organizing map
Author :
Shah-Hosseini, Hamed ; Safabakhsh, Reza
Author_Institution :
Comput. Eng. Dept., Amirkabir Univ. of Technol., Tehran, Iran
fDate :
10/1/2002 12:00:00 AM
Abstract :
In this paper, a Growing TASOM (Time Adaptive Self-Organizing Map) network called "GTASOM" along with a peak finding process is proposed for automatic multilevel thresholding. The proposed GTASOM is tested for image segmentation. Experimental results demonstrate that the GTASOM is a reliable and accurate tool for image segmentation and its results outperform other thresholding methods.
Keywords :
image segmentation; self-organising feature maps; GTASOM; Growing TASOM; automatic multilevel thresholding; growing time adaptive self-organizing map; image segmentation; peak finding process; Adaptive systems; Clustering algorithms; Histograms; Image segmentation; Lattices; Neurons; Principal component analysis; Process design; Quantization; Testing;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2002.1039209
