Title :
An Adaptive Algorithm for License Plate Orientation and Character Segmentation
Author :
Li, Bo ; Zeng, Zhiyuan ; Zhou, Jianzhong ; Zhou, Mu
Abstract :
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.
Keywords :
character recognition; edge detection; image colour analysis; image matching; image segmentation; mathematical morphology; traffic engineering computing; adaptive algorithm; color binarization; color-reversing judgment; edge density template matching; edge grayscale jump characteristics; license plate character segmentation; license plate recognition system; mathematical morphology; sobel color edge detection; Adaptive algorithm; Conferences; Convolution; Detectors; Gray-scale; Image color analysis; Image edge detection; Image segmentation; Licenses; Linearity; Character segmentation; Image processing; License plate orientation; License plate recognition;
Conference_Titel :
Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3490-9
DOI :
10.1109/PACIIA.2008.186
