License plate detection using Cluster Run Length Smoothing Algorithm (CRLSA)

Siti Norul Huda Sheikh Abdullah, Marzuki Khalid, Rubiyah Yusof, Khairuddin Omar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. In this paper, an automatic license plate recognition system is proposed for Malaysian vehicles with standard license plates based on image processing, clustering, feature extraction and neural networks.The image processing library is developed in-house which referred to as Vision System Development Platform (VSDP). Fixed filter, Minimum filter, Median Filter and Homomorphic Filtering are used in image enhancement process. After applying image enhancement, the image is segmented using blob analysis, horizontal scan line profiles, clustering and run length smoothing algorithm approach to identify the location of the license plate. Thoroughly each image is transformed into blob objects and its important information such as total of blobs, location, height and width, are being analyzed for the purpose of cluster exercising and choosing the best cluster with winner blobs. Here, new algorithm called Cluster Run Length Smoothing Algorithm (CRLSA) approach was applied to locate the license plate at the right position. CRLSA consisted of two separate new proposed algorithm which applied new edge detector algorithm using 3×3 kernel masks and 128 grayscale offset plus a new way (3D method) to calculate run length smoothing algorithm (RLSA), which can improve clustering techniques in segmentation phase. Three separate experiments were performed; Cluster and Threshold value 130 (CT 130) and CRLSA with Threshold value 1 (CCT1). From those experiments, analysis of error tables based on segmentation errors were constructed. The prototyped system has an accuracy more than 96% and suggestions to further improve the system are discussed in this paper pertaining to analysis of the error.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2007
Pages323-328
Number of pages6
Publication statusPublished - 2007
EventIASTED International Conference on Artificial Intelligence and Applications, AIA 2007 - Innsbruck
Duration: 12 Feb 200714 Feb 2007

Other

OtherIASTED International Conference on Artificial Intelligence and Applications, AIA 2007
CityInnsbruck
Period12/2/0714/2/07

Fingerprint

Image enhancement
Image processing
Median filters
Feature extraction
Masks
Experiments
Detectors
Neural networks

Keywords

  • Clustering
  • License plate recognition
  • Run length smoothing algorithm
  • Thresholding

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

Cite this

Sheikh Abdullah, S. N. H., Khalid, M., Yusof, R., & Omar, K. (2007). License plate detection using Cluster Run Length Smoothing Algorithm (CRLSA). In Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2007 (pp. 323-328)

License plate detection using Cluster Run Length Smoothing Algorithm (CRLSA). / Sheikh Abdullah, Siti Norul Huda; Khalid, Marzuki; Yusof, Rubiyah; Omar, Khairuddin.

Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2007. 2007. p. 323-328.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sheikh Abdullah, SNH, Khalid, M, Yusof, R & Omar, K 2007, License plate detection using Cluster Run Length Smoothing Algorithm (CRLSA). in Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2007. pp. 323-328, IASTED International Conference on Artificial Intelligence and Applications, AIA 2007, Innsbruck, 12/2/07.
Sheikh Abdullah SNH, Khalid M, Yusof R, Omar K. License plate detection using Cluster Run Length Smoothing Algorithm (CRLSA). In Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2007. 2007. p. 323-328
Sheikh Abdullah, Siti Norul Huda ; Khalid, Marzuki ; Yusof, Rubiyah ; Omar, Khairuddin. / License plate detection using Cluster Run Length Smoothing Algorithm (CRLSA). Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2007. 2007. pp. 323-328
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