Title :
Multi-target car license plate detection from complex environment
Author :
Tung-Snou Chen ; Hsien-Hu Wu ; Ching-Hao Lai
Author_Institution :
Nat. Taichung Inst. of Technol., Taiwan
Abstract :
Summary form only given. In recent years, there has been much research on license plate recognition (LPR), and LPR systems are used frequently. The three major parts in LPR are plate detection, character segmentation and character recognition. A smart and simple algorithm for LPR is presented. This algorithm can be applied for multiple license plate detection. There may be many cars in an image with a complex background. We study how to extract license plates effectively. We use edge detection, image dilation, block filtration and license proportion checking to extract plates accurately. Experimental results show that the algorithm is robust in extracting multiple plates in an image with a complex background. Results yield more than 86.67% correct location of license plates.
Keywords :
edge detection; feature extraction; image segmentation; object detection; object recognition; block filtration; character recognition; character segmentation; complex background; edge detection; image dilation; license plate recognition; license proportion checking; multi-target car license plate detection; plate detection; Character recognition; Filtration; Image edge detection; Image segmentation; Licenses; Robustness;
Conference_Titel :
Nonlinear Signal and Image Processing, 2005. NSIP 2005. Abstracts. IEEE-Eurasip
Conference_Location :
Sapporo
Print_ISBN :
0-7803-9064-4
DOI :
10.1109/NSIP.2005.1502281