Automatic Number Plate Recognition

Shilpa Pawar¹, Prabhakar Singh², Shailender Singh³, Roshan Kumar⁴

^1,2,3,4Savitribai Phule Pune University

Abstract

The main focus in this research paper is to experiment deeply with, and find alternative solutions to the image segmentation and character recognition problems within the License Plate Recognition framework. Three main stages are identified in such applications. First, it is necessary to locate and extract the license plate region from a larger scene image. Second, having a license plate region to work with, the alphanumeric characters in the plate need to be extracted from the background. Third, deliver them to an character system (BOX APPROACH)for recognition. In order to identify a vehicle by reading its license plate successfully, it is obviously necessary to locate the plate in the scene image provided by some acquisition system (e.g. video or still camera). Locating the region of interest helps in dramatically reducing both the computational expense and algorithm complexity. For example, a currently common 1024x768 resolution image contains a total of 786, 432pixels, while the region of interest (in this case a license plate) may account for only 10% of the image area. Also, the input to the following segmentation and recognition stages is simplified, resulting in easier algorithm design and shorter computation times. The paper mainly work with the standard license plates but the techniques, algorithms and parameters that is be used can be adjusted easily for any similar number plates even with other alpha-numeric set.

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Cite this Article as Follows

Shilpa Pawar, Prabhakar Singh, Shailender Singh, Roshan Kumar. Automatic Number Plate Recognition. International Conference on Inter Disciplinary Research in Engineering and Technology 2015. Vol. 1. Chennai: Association of Scientists, Developers and Faculties, 2015. 222-224. Print.