Home   >   CSC-OpenAccess Library   >    Manuscript Information
A Novel Multiple License Plate Extraction Technique for Complex Background in Indian Traffic Conditions
Chirag N. Paunwala, Suprava Patnaik
Pages - 106 - 118     |    Revised - 30-04-2010     |    Published - 10-06-2010
Volume - 4   Issue - 2    |    Publication Date - May 2010  Table of Contents
Segmentation, Ultrasound, Speckle Noise, Artifacts, Ionizing radiations
License plate recognition (LPR) is one of the most important applications of applying computer techniques towards intelligent transportation systems (ITS). In order to recognize a license plate efficiently, location and extraction of the license plate is the key step. Hence finding the position of a license plate in a vehicle image is considered to be the most crucial step of an LPR system, and this in turn greatly affects the recognition rate and overall speed of the whole system. This paper mainly deals with the detecting license plate location issues in Indian traffic conditions. The vehicles in India sometimes bare extra textual regions such as owner’s name, symbols, popular sayings and advertisement boards in addition to license plate. Situation insists for accurate discrimination of text class and fine aspect ratio analysis. In addition to this additional care taken up in this paper is to extract license plate of motorcycle (size of plate is small and double row 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 frame under consideration. Disparity of aspect ratios is a typical feature of Indian traffic. Proposed method aims at identifying region of interest by performing a sequence of directional segmentation and morphological processing. Always the first step is of contrast enhancement, which is accomplished by using sigmoid function. In the subsequent steps, connected component analysis followed by different filtering techniques like aspect ratio analysis and plate compatible filter technique is used to find exact license plate. The proposed method is tested on large database consisting of 750 images taken in different conditions. The algorithm could detect the license plate in 742 images with success rate of 99.2%.
CITED BY (23)  
1 Panchal, T., Patel, H., & Panchal, A. (2016). License Plate Detection Using Harris Corner and Character Segmentation by Integrated Approach from an Image. Procedia Computer Science, 79, 419-425.
2 Naubadkar, S., & Meera, A. (2015). Enhanced Algorithm For Tracking number Plate From Vehicle Using Blob Analysis.
3 Peer, S., & Mishra, A. Tracking and segmentation of number plates of Indian vehicles using matlab.
4 Bernal, E. A. (2014). U.S. Patent No. 8,823,798. Washington, DC: U.S. Patent and Trademark Office.
5 Paunwala, C. N., & Patnaik, S. Automatic License Plate Localization Using Intrinsic Rules Saliency. International Journal of Advanced Computer Science and Applications Special Issue on Image Processing and Analysis.
6 Kaur, S., Kaur, K., & Singh, R. (2014). An Automatic System for Detecting the Vehicle Registration Plate from Video in Foggy and Rainy Environments using Restoration Technique. International Journal of Computer Applications, 97(20), 14-19.
7 Gupta, P., Purohit, G. N., & Rathore, M. (2014). Number Plate extraction using Template matching technique. International Journal of Computer Applications, 88(3).
8 Linxin You. (2013). Defaced license plate is not clear and high performance classification system of identification.
9 Prajapati, A. M., Bhomia, Y., & Kajla, A. Optimization of Feature Extraction Algorithm for License Plate of Vehicle, Detection Using Histogram Method.
10 Thourn, K. Cambodian Vehicle License Plate Localization.
11 Chen, Y. T., Chuang, J. H., Teng, W. C., Lin, H. H., & Chen, H. T. (2012, May). Robust license plate detection in nighttime scenes using multiple intensity IR-illuminator. In Industrial Electronics (ISIE), 2012 IEEE International Symposium on (pp. 893-898). IEEE.
12 Paunwala, C. N., & Patnaik, S. (2012). An adaptive integrated rule-based algorithm for license plate localization. Opto-Electronics Review, 20(4), 323-334.
13 Dahotre, A., Malushte, R., Karande, M., & Bamb, H. Automatic Toll Collection System using OCR.
14 Patel Fenil, S., Campus, M., Bardoli, U. T. U., & Patel Pratik, J. Automatic License Plate Recognition.
15 Mukherjee, S., & Poonia, A. S. Automatic Number Plates Recognition Using Improved Algorithms.
16 Modi, N. D., Modi, C. K., Paunwala, C. N., & Patnaik, S. (2011, June). Skew correction for vehicle license plates using principal component of Harris Corner Feature. In Communication Systems and Network Technologies (CSNT), 2011 International Conference on (pp. 339-343). IEEE.
17 Gaur, S. B., & Vajpai, J. (2011). Comparison of edge detection techniques for segmenting car license plates. Int. J. Comput. Appl. Electron. Inf. Commun. Eng, 5, 8-12.
18 Boggavarapu, L. N. P., Vaddi, R. S., Vankayalapati, H. D., & Anne, K. R. (2011). Edge Detection Using CNN for the Localization of Non-standard License Plate. In Computer Recognition Systems 4 (pp. 685-695). Springer Berlin Heidelberg.
19 Boggavarapu, L. N. P., Munagala, J. K., Vaddi, R. S., & Anne, K. R. (2011, April). Localization of non-standard licence plate using morphological operations—An Indian context. In Electronics Computer Technology (ICECT), 2011 3rd International Conference on (Vol. 3, pp. 65-69). IEEE.
20 Abraham, V. Z., Kurian, B., & Rajesh, N. (2011, December). Multiple license plate recognition for intelligent traffic management. In India Conference (INDICON), 2011 Annual IEEE (pp. 1-4). IEEE.
21 Vaddi, R. S., Boggavarapu, L. N. P., Vankayalapati, H. D., & Anne, K. R. (2011, April). Cellular neural network based pre-processing for localization of non standard licence plate. In Electronics Computer Technology (ICECT), 2011 3rd International Conference on (Vol. 1, pp. 407-411). IEEE.
22 Paunwala, C. N., & Patnaik, S. (2011). Scene-Retrieved Attributes for Automatic License Plate Localization. Cybernetics and Systems, 42(8), 567-584.
23 Wu, P. W. (2011). Generalized Spatial Cognition Model and its application in the field of intelligent robots. Thesis, Institute of Mechanical Engineering, National Taiwan University, 1-112.
1 Google Scholar 
2 ScientificCommons 
3 Academic Index 
4 CiteSeerX 
5 refSeek 
6 iSEEK 
7 Socol@r  
8 ResearchGATE 
9 Bielefeld Academic Search Engine (BASE) 
10 Scribd 
11 WorldCat 
12 SlideShare 
14 PdfSR 
B. Hongliang and L. Changping. “A Hybrid License Plate Extraction Method Based on Edge Statistics and Morphology,” in Proc. ICPR, pp. 831–834, 2004.
C. Anagnostopoulos, I. Anagnostopoulos, E. Kayafas, and V. Loumos. “A License Plate Recognition System for Intelligent Transportation System Applications”, IEEE Trans. Intell. Transp. Syst., 7(3), pp. 377– 392, Sep. 2006.
C. Wu, L. C. On, C. H. Weng, T. S. Kuan, and K. Ng, “A Macao License Plate Recognition system,” in Proc. 4th Int. Conf. Mach. Learn. Cybern., China, pp. 4506–4510, 2005.
Ching-Tang Hsieh, Yu-Shan Juan, Kuo-Ming Hung, “Multiple License Plate Detection for Complex Background”, Proceedings of the 19th International Conference on Advanced Information Networking and Applications, pp.389-392, 2005.
D. Comaniciu and P. Meer. “Mean shift: A Robust Approach Towards Feature Space Analysis,” IEEE Trans. Pattern Anal. Mach. Intell., 24(5), pp. 603–619, May 2002
F. Martin, M. Garcia and J. L. Alba. “New methods for Automatic Reading of VLP’s (Vehicle License Plates),” in Proc. IASTED Int. Conf. SPPRA, pp: 126-131, 2002.
Feng Yang, Zheng Ma. “Vehicle License Plate Location Based on Histogramming and Mathematical Morphology”, Automatic Identification Advanced Technologies, 2005. pp:89 – 94, 2005
Feng Yang,Fan Yang. “Detecting License Plate Based on Top-hat Transform and Wavelet Transform”, ICALIP, pp:998-2003, 2008
H. Mahini, S. Kasaei, F. Dorri, and F. Dorri. “An efficient features–based license plate localization method,” in Proc. 18th ICPR, Hong Kong, vol. 2, pp. 841–844, 2006.
H.-J. Lee, S.-Y. Chen, and S.-Z. Wang, “Extraction and Recognition of License Plates of Motorcycles and Vehicles on Highways,” in Proc. ICPR, pp. 356–359, 2004.
J. Kong, X. Liu, Y. Lu, and X. Zhou. “A novel license plate localization method based on textural feature analysis,” in Proc. IEEE Int. Symp. Signal Process. Inf. Technol., Athens, Greece, pp. 275–279, 2005.
J. Sauvola and M. Pietikäinen, “Adaptive Document Image Binarization,” Pattern Recognition, 33(2), pp. 225–236, Feb. 2000.
M. Wu, L. Wei, H. Shih and C. C. Ho. “License Plate Detection Based on 2-Level 2D Haar Wavelet Transform and Edge Density Verification”, IEEE International Symposium on Industrial Electronics (ISlE), pp: 1699-1705, 2009.
N.Otsu. “A Threshold Selection Method from Gray-Level Histograms”, IEEE Trans. Sys., Man and Cybernetics, 9(1), pp.62-66, 1979.
Naglaa Yehya Hassan, Norio Aakamatsu, “Contrast Enhancement Technique of Dark Blurred Image”, IJCSNS International Journal of Computer Science and Network Security, 6(2), pp:223-226, February 2006
P. V. Suryanarayana, S. K. Mitra, A. Banerjee and A. K. Roy. “A Morphology Based Approach for Car License Plate Extraction”, IEEE Indicon, vol.-1, pp: 24-27, 11 - 13 Dec. 2005
R.C. Gonzalez, R.E. Woods, “Digital Image Processing”, PHI, second edd, pp: 519:560 (2006)
Saeed Rastegar, Reza Ghaderi, Gholamreza Ardeshipr & Nima Asadi, “An intelligent control system using an efficient License Plate Location and Recognition Approach”, International Journal of Image Processing (IJIP) Volume(3), Issue(5), pp:252-264, 2009
Shih-Chieh Lin, Chih-Ting Chen , “Reconstructing Vehicle License Plate Image from Low
T. D. Duan, T. L. H. Du, T. V. Phuoc, and N. V. Hoang, “Building an automatic vehicle license-plate recognition system,” in Proc. Int. Conf. Computer Sci. (RIVF), pp. 59–63, 2005.
W. Jia, H. Zhang, X. He, and M. Piccardi, “Mean shift for accurate license plate localization,” in Proc. 8th Int. IEEE Conf. Intell. Transp. Syst., Vienna, pp. 566–571, 2005.
W. Wen, X. Huang, L. Yang, Z. Yang and P. Zhang, “The Vehicle License Plate Location Method Based-on Wavelet Transform”, International Joint Conference on Computational Sciences and Optimization, pp:381-384, 2009
X. Shi,W. Zhao, and Y. Shen, “Automatic License Plate Recognition System Based on Color Image Processing”, 3483, Springer-Verlag, pp. 1159–1168, 2005.
Y. Cheng, “Mean shift, mode seeking, and clustering,” IEEE Trans. Pattern Anal. Mach. Intell., 17(8), pp. 790–799, Aug. 1995.
Mr. Chirag N. Paunwala
- India
Suprava Patnaik
- India

View all special issues >>