Automated Car Number Plate Recognition System using K-Nearest Neighbor
Divya Narula1, Manish Mahajan2, Kamalinder Kaur3
1Divya Narula. Department of Computer Science in 2016 from Gurukul Vidyapeeth Institute of Engineering and Technology Banur, Mohali, India.
2Dr. Manish Mahajan. Professor at Computer Science Engineering department of Chandigarh Engineering College, Landran, Mohali., Punjab. India.
3Kamalinder Kaur. Currently working as Assistant Professor in Chandigarh Group of Colleges, Landran, Mohali, Punjab, India.
Manuscript received on 05 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 1113-1117 | Volume-8 Issue-10, August 2019 | Retrieval Number: J87820881019/2019©BEIESP | DOI: 10.35940/ijitee.J8782.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Automatic number plate recognition (ANPR) is a mass reconnaissance strategy that utilizations optical character recognition on images to peruse the license plates on vehicles. The car number plate detection has the various phases like pre-processing, segmentation and classification. In the previous work, the morphological operation is applied for the car number plate detection. The morphological operation has the low accuracy for the car number plate detection. In the proposed work, the region based segmentation and K-nearest neighbor classification is applied for the character recognition. The proposed is implemented in MATLAB and results are analyzed in terms of accuracy.
Keywords: Number Plate Detection, KNN, K-mean, Morphological Operation.
Scope of the Article: Pattern Recognition