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• W67744807 abstract "Real Time Detection and Recognition of License Plate in Bengali Md. Mahmudul Hasan ∗1 , Md. Humayun Kabir †1 and M. Ameer Ali ‡2 Department of CSE, BUET, Dhaka, Bangladesh Department of CSE, East West University, Dhaka, Bangladesh Abstract Automatic license plate detection and recognition has numerous applications. A large number of schemes have already been proposed in order to make the detection and recognition process efficient. However, a very little work has been done on Bengali license plate recognition. Wide variation among the license plate patterns, complex background, and the difficulty in segmenting Bengali characters of Bangladeshi license plates make it inefficient to use the existing algorithms. In this paper, we propose a solution for Bengali license plate detection and recognition. We use three stages of conventional license plate recognition system. However, we propose new algorithm in each stage, which are effective for Bengali license plate detection and recognition. We tested our algorithms for over 250 images taken from the road. We achieve over 95% success in Bengali license plate recognition. Introduction Automated License Plate Recognition (ALPR) is one of the important module of Intelligent Transportation System (ITS). Research works [1] and [2] have listed many applications of ALPR, such as electronic payment systems (toll payment or parking), free-way and aerial management for traffic surveillance, recovering stolen cars, identifying cars with an open warrant for arrest, catching speeders by comparing the average time it takes to get from one stationary camera to another stationary camera, determining what cars do or do not belong to a parking garage, expediting parking by eliminating the need for human confirmation of parking passes etc. Most of the ALPR systems use three stages of processing [1]. In the first stage, the location of the license plate is determined from the input image. The input may be a video sequence or a still image. These image may be a binary, a grey scale, or a color image. Therefore, either binary or grey scale or color image processing technique is used in this stage. Morphological analysis [6], vertical and horizontal edge detection [16] [7], connected component analysis [17], spatial measurement [17], etc. are the most widely used binary image processing techniques. Image transformation [19], region segmentation [20], [3], hierarchical representations [18], etc. are widely used grey scale image processing techniques. Research works [11] and [12] used color image processing. Fuzzy set theory was used in research works [22] and [21]. In the second stage, the characters inside the license plate region are segmented. Binary and grey scale image processing techniques are mainly used to segment the characters. In the binary image processing techniques, several methods such as horizontal and vertical projection [24] [23] [11], mathematical morphology [25] [24], and contours [26] are used. Methods like local and adaptive threshold [28] [27], histogram processing [30] [29], classifiers [31] [32] etc. are the most commonly used grey scale image processing techniques to segment the characters. The third and the last stage in license plate detection and recognition system is the character recognition stage. Different types of neural networks, such as Hidden Markov Model (HMM) [35], Support Vector Machine (SVM) [18], and Artificial Neural Network (ANN) [36] [22] [30] are used to classify the characters. Other than neural networks, pattern or template matching techniques [34] [33] are also used to recognize the characters. Although a large number of research works have already been conducted on automatic license plate detection and recognition system, a generalized system is still missing [3]. Most of the existing systems perform well under some specific constraints. These constraints are certain distance from the camera [6] [7], speed of the vehicle [8], illumination conditions [9] [10], color of the vehicle [11] [12], camera positions [13] etc. Moreover, these ∗ mhasa004@ucr.edu. This author is now affiliated with Dept. of CSE, University of California, Riverside. † mhkabir@cse.buet.ac.bd ‡ ameer7302002@yahoo.com" @default.
• W67744807 created "2016-06-24" @default.
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• W67744807 date "2013-11-25" @default.
• W67744807 modified "2023-09-26" @default.
• W67744807 title "Real Time Detection and Recognition of License Plate in Bengali" @default.
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