DocumentCode
3113841
Title
Peak detection in Hough transform via self-organizing learning
Author
Choy, Cliflord Sze-Tsaiz ; Ser, Pui-Kin ; Siu, Wan-chi
Author_Institution
Dept. of Electron. Eng., Hong Kong Polytech., Kowloon, Hong Kong
Volume
1
fYear
1995
fDate
30 Apr-3 May 1995
Firstpage
139
Abstract
In this paper, we suggest a novel concept of applying the self-organizing map (SOM) in the Hough domain for a significant reduction of the Hough space. By using the SOM as the output space of the generalized Hough transform, the conventional 4-D Hough domain is replaced by a 10×10 map, organized in a rectangular grid. Experimental results indicate high accuracy in voting is attainable despite its small memory requirement
Keywords
Hough transforms; feature extraction; learning (artificial intelligence); self-organising feature maps; 4-D Hough domain; Hough transform; learning; memory; peak detection; rectangular grid; self-organizing map; voting; Analog circuits; Costs; Councils; Feature extraction; Genetic expression; Neural networks; Neurons; Pixel; Testing; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-2570-2
Type
conf
DOI
10.1109/ISCAS.1995.521470
Filename
521470
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