An Adaptive Algorithm for License Plate Orientation and Character Segmentation

Based on the sharing features of a variety of license plates (LP), the vertical edge was first detected by sobel color edge detector. Then, some approaches were adopted to adaptively remove the invalid edge regarding the characteristics of edge grayscale jump and edge density, so that the regions having features of LP were preserved. Next, by edge density template matching and the mean and variance of grayscale jump points, the LP region was rapidly searched. Then, color-reversing judgment was conducted by color analysis, and binarization was done based on edge detection. Afterward, characters were segmented by means of mathematical morphology (MM) and connected components analysis. With an abundant samples verified in dark hours and daytime under real conditions, the experiment indicates that it is feasible to adopt this algorithm in license plate recognition system(LPRS) to achieve accuracy and adaptability.