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A Novel Multiple License Plate Extraction Technique for Complex Background in Indian Traffic Conditions

Author(s): Chirag N. Paunwala, Suprava Patnaik

Journal: International Journal of Image Processing
ISSN 1985-2304

Volume: 4;
Issue: 2;
Start page: 106;
Date: 2010;
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Keywords: License plate recognition | sigmoid function | Horizontal projection | Mathematical morphology | Aspect ratio analysis | Plate compatible filter.

License plate recognition (LPR) is one of the most important applications ofapplying computer techniques towards intelligent transportation systems (ITS). Inorder to recognize a license plate efficiently, location and extraction of the licenseplate is the key step. Hence finding the position of a license plate in a vehicleimage is considered to be the most crucial step of an LPR system, and this inturn greatly affects the recognition rate and overall speed of the whole system.This paper mainly deals with the detecting license plate location issues in Indiantraffic conditions. The vehicles in India sometimes bare extra textual regions,such as owner’s name, symbols, popular sayings and advertisement boards inaddition to license plate. Situation insists for accurate discrimination of text classand fine aspect ratio analysis. In addition to this additional care taken up in thispaper is to extract license plate of motorcycle (size of plate is small and doublerow plate), car (single as well as double row type), transport system such as bus,truck, (dirty plates) as well as multiple license plates present in an image frameunder consideration. Disparity of aspect ratios is a typical feature of Indiantraffic. Proposed method aims at identifying region of interest by performing asequence of directional segmentation and morphological processing. Always thefirst step is of contrast enhancement, which is accomplished by using sigmoidfunction. In the subsequent steps, connected component analysis followed bydifferent filtering techniques like aspect ratio analysis and plate compatible filtertechnique is used to find exact license plate. The proposed method is tested onlarge database consisting of 750 images taken in different conditions. Thealgorithm could detect the license plate in 742 images with success rate of99.2%.
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