An Efficient Approach for Automatic Number Plate Recognition System under Image Processing
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Abstract
Automatic Number Plate Recognition (ANPR) system is an image processing technology that identifies the vehicles by tracking their number plate without direct human intervention and an application of computer vision. ANPR is an important method used in Intelligent Transportation System (ITS). The four phases of the ANPR system: Image acquisition and pre-processing, number plate extraction, character segmentation and character recognition are discussed in this paper. Number Plate Extraction is most crucial step in the ANPR system which affects the overall accuracy and efficiency of whole ANPR system. The quality of acquired vehicle image is a major factor in the success of ANPR. In this paper we have proposed an efficient approach for ANPR in which the input vehicle image is firstly pre-processed using iterative bilateral filter and adaptive histogram equalization and number plate is extracted from pre-processed vehicle image using morphological operations, image subtraction, thresholding, sobel edge detection and boundary box analysis. We compared the result of our proposed approach with existing method of ANPR.
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Keywords - Automatic number plate recognition, histogram equalization, adaptive histogram equalization, iterative bilateral filter, median filter, number plate extraction, morphological operations, image subtraction, thresholding, sobel edge detection, connected component analysis, boundary box analysis, character segmentation, character normalization, template matching, character recognition.
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