Title :
Morphological traffic sign recognitions
Author :
Jiang, Gang Yi ; Choi, Tae Young ; Zheng, Yi
Author_Institution :
Dept. of Electron. Eng., Hangzhou Univ., China
Abstract :
The main attentions are focused on a binary machine vision problem, e.g., morphological traffic sign recognition. In order to recognize informational inner sign shapes of Korean traffic signs on roads, four quantitative similarity measures are developed, which are based on mathematical morphology and binary rank statistics. Using them, maximum similarity or minimum distance matching algorithms are proposed. Simulation results show that the algorithms are efficient and robust to noise
Keywords :
computer vision; image matching; image recognition; mathematical morphology; road traffic; statistical analysis; binary machine vision; binary rank statistics; mathematical morphology; maximum similarity matching algorithms; minimum distance matching algorithms; morphological traffic sign recognition; noise robustness; quantitative similarity measures; roads; simulation results; traffic sign shape recognition; Computer vision; Humans; Image analysis; Morphology; Roads; Shape measurement; Signal processing; Signal processing algorithms; Statistics; Traffic control;
Conference_Titel :
Signal Processing, 1996., 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-2912-0
DOI :
10.1109/ICSIGP.1996.567319
