Design of an efficient real-time algorithm using reduced feature dimension for recognition of speed limit signs.
We propose a real-time algorithm for recognition of speed limit signs from a moving vehicle. Linear Discriminant Analysis (LDA) required for classification is performed by using Discrete Cosine Transform (DCT) coefficients. To reduce feature dimension in LDA, DCT coefficients are selected by a devised discriminant function derived from information obtained by training. Binarization and thinning are performed on a Region of Interest (ROI) obtained by preprocessing a detected ROI prior to DCT for further reduction of computation time in DCT. This process is performed on a sequence of image frames to increase the hit rate of recognition. Experimental results show that arithmetic operations are reduced by about 60%, while hit rates reach about 100% compared to previous works.
Department of Electronic Engineering, Sogang University, Seoul 121-742, Republic of Korea.
Hanmin
H
Cho
Samsung Techwin R&D Center, Security Solution Division, 701 Sampyeong-dong, Bundang-gu, Seongnam-si, Gyeonggi 463-400, Republic of Korea.
Seungwha
S
Han
Department of Electronic Engineering, Sogang University, Seoul 121-742, Republic of Korea.
Sun-Young
SY
Hwang
D000465:Algorithms; D003201:Computers; D016002:Discriminant Analysis; D016014:Linear Models; D010363:Pattern Recognition, Automated; D012449:Safety; D012984:Software; D014186:Transportation