License Plate Detection using OCR with KNN
D. Hareesha1, V. Susmitha Rani2, S.Gopi Chand3
1D. Hareesha*, Assistant Professor, Department of ECE, Prasad V. Potluri Siddhartha Institute of Technology, Kanuru, Vijayawada, India.
2V. Susmitha Rani, Department of ECE, Prasad V. Potluri Siddhartha Institute of Technology, Kanuru, Vijayawada, India.
3Simhadri Gopi Chand, Department of ECE, Prasad V. Potluri Siddhartha Institute of Technology, Kanuru, Vijayawada, India.
Manuscript received on March 30, 2020. | Revised Manuscript received on April 05, 2020. | Manuscript published on April 30, 2020. | PP: 1087-1088 | Volume-9 Issue-4, April 2020. | Retrieval Number: D6738049420/2020©BEIESP | DOI: 10.35940/ijeat.D6738.049420
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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: This paper presents associate in nursing economical methodology for the detection of vehicle plate by accurately localizing number plates from pictures. A straight forward downscaling of image methodology is projected initial to boost the speed of vehicle plate localization while not reducing the detection performance compared thereupon victimization the first image. Moreover, a completely unique Line Density Filter (LDF) methodology is projected to identify desired regions and eventually reducing the realm to be analysed for vehicle plate detection. Also, a vehicle plate classifier supported SVMs victimization color prominence options employed to spot the vehicle plate from the image. For performance check, a dataset having thirty pictures taken from completely different scenes under different conditions is additionally used. The data set demonstrates that the projected methodology performs well in terms of accuracy and run-time potency.
Keywords: Methodology, Pictures taken from completely different.