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::A new method of vehicle license plate location under complex scenesOutlineINTRODUCTIONLICENSE PLATE LOCATION SYSTEMImage pre-processingImage horizontal differencesGradient Image adaptive threshold segmentationMorphological operationsRegion mergingThe achievement of positioning through regional searchEXPERIMENT AND ANALYSISCONCLUSIONSREFERENCESINTRODUCTIONA LPR(license plate recognition) system is mainly composed of three processing modules:license plate locationcharacter segmentation character recognitionLocate various kinds of license plates in a short time and meet the needs of real-time location of vehiclesLICENSE PLATE LOCATION SYSTEM

The flowchart of license plate locationImage pre-processingGray-scale processing of the images

Image horizontal differencesgray gradient image G

Gray gradient imageGradient Image adaptive threshold segmentation(1/4)Steps are as follows

the initial weights factor =0.6Weight increment factor =0.05Gw is the maximum of every row in gradient image as experience value and needs no modification

(a)Gradient Image adaptive threshold segmentation(2/4)(b)Segment G by making use of T

Gradient Image adaptive threshold segmentation(3/4)(c) 1.opening operation of G by using 10x10 structuring element and eliminate some noise points 2.connected region of license plate can be formed through closure operation by utilizing 1515 structuring element(d)Calculate the density of white points in the image w=Count/(H*W)

Gradient Image adaptive threshold segmentation(4/4)(e)Adopt 1=0.03 2=0.08.If w2 ,then = - . The algorithm turn to step a),otherwise, the process ends

Morphological operations

further morphological operation to reduce the number of irrelevant regionsSteps are as followsSmall noise regions are dispelled through morphological opening operation with 20x20 structural elementserosion and inflation operation are conducted by using 6x6 structural elementsDilation is conducted by making use of 25x5 structural elements

Region mergingThe principle of region merging is:if the absolute offset of rows and columns in two neighbor regions are within certain range

(a)The result of further morphological processing(b)The result of region merging(a)(b)The achievement of positioning through regional searchSteps are as followsthe aspect ratio is between 2.2 and 3.5background color and word color, we make binaryzation of every candidate region with the method of global Otsu methodproportion of target points in the overall candidate region this proportion is usually between 0.25 and 0.65 w=count/(h*w)

EXPERIMENT AND ANALYSIS(1/2)

REGIONS EXPERIMENT RESULTSEXPERIMENT AND ANALYSIS(2/2)

The results of license plate location under different conditionsCONCLUSIONSadvantage on the location of low-quality license plate shot in the complex conditions of changing light, noisy environment and far distancesREFERENCES[1] Wenju Li, Dequn Liang and Qi Zhang , A novel approach for vehicle license plate location based on edge-color pair, Chinese Journal of Computer, vol.27,2004,pp.204-208.[2] Jie Guo and Pengfei Shi, Color and texture analysis based vehicle license plate location, Journal of Image and Graphics,vol.7,2002,pp.426-427.[3] Park S H,Kim K I and Jung K, Locating car license plates using neural networks,Electronics Letters,vol.35,1999,pp.1475-1477.[4] Weiqi Yuan and Liang Zhang,An improved vehicle plate location method based on block segmentation,, ACTA AUTOMATICA SINICA,vol.33, 2007,pp.768-770.[5] Ichen Tsai, Juichen Wu, Recognition of Vehicle License Plates from a Video Sequence, IAENG International Journal of Computer Science,vol.36,2009.[6] Hsieh J W,Yu S H and Chen Y S, Morphology based license plate detection from complex scenes,Proceedings of 16th International Conference on Pattern Recognition(ICPR02),IEEE Press,2002,pp.176-179.[7] Yue Lu ,Dongjian He and Xiao He, Fast algorithm for vehicle license plate localization based on scan line and feature selection,Computer Engineering and Design,vol.29,2008,pp.5125-5128.