Title :
Pattern Recognition Based on Relative Position of Local Features Using Self-Organizing Map
Author :
Horio, Keiichi ; Aikawa, Akira ; Yamakawa, Takeshi
Author_Institution :
Graduate Sch. of Life Sci. & Syst. Eng., Kyushu Inst. of Technol.
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
In this paper, we propose a new pattern recognition method based on relative position of local feature. In the visual system of human, the local features such as lines and curves are extracted, and they are integrated. In the proposed method, relative position of the gazing points which include local features are extracted using self-organizing map. A template matching concerning the local features is used for recognizing the patterns. The effectiveness of the proposed method is verified by applying it to MNIST handwritten digits database
Keywords :
feature extraction; image matching; image recognition; self-organising feature maps; gazing points; image recognition method; local feature extraction; local feature relative position; pattern recognition; self-organizing map; template matching; Feature extraction; Humans; Image edge detection; Image recognition; Neural networks; Pattern matching; Pattern recognition; Spatial databases; Visual databases; Visual system;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.329