An Approach towards Detection of Indian Number Plate from Vehicle
Sourav Roy1, Amitava Choudhury2, Joydeep Mukherjee3
1Sourav Roy, Perusing M.Tech Degree, Department of Education Technology, Jadavpur University, Kolkata (West Bengal), India.
2Amitava Choudhury, Perusing M.Tech Degree, Department of Education Technology, Jadavpur University, Kolkata (West Bengal), India.
3Joydeep Mukherjee, Assistant Professor, Department of Education Technology, Jadavpur University, Kolkata (West Bengal), India.
Manuscript received on 12 March 2013 | Revised Manuscript received on 21 March 2013 | Manuscript Published on 30 March 2013 | PP: 241-245 | Volume-2 Issue-4, March 2013 | Retrieval Number: D0572032413/13©BEIESP
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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: Vehicle number plate recognition is the most interesting and challenging research topic from past few years. It is shown that the number plates are different shape and size and also have different color in different countries. In India the most common vehicle number plate used yellow or while as background and black used as foreground color. In this paper we proposed a system to localization of number plate mainly for the vehicles in West Bengal (India) and segmented the numbers as to identify each number separately. This paper presents an approach based on simple and efficient morphological operation and sobel edge detection method. We also presents a simple approach to segmented all the letters and numbers used in the number plate. After reducing noise from the input image we try to enhance the contrast of the binarized image using histogram equalization. We mainly concentrate on two steps; one is to locate the number plate and second is to segment all the number and letters to identify each number separately. The project develops by using MATLAB7.4.0.
Keywords: Number Plate Localization, Morphological Operation, Character Segmentation, Thresholding, Edge Detection.
Scope of the Article: Network Operations & Management