Design of an Efficient Real-Time Algorithm Using Reduced Feature Dimension for Recognition of Speed Limit Signs

Abstract EN

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.