Car License Plate Detection Based on Line Segments

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1 , pp Car License Plate Detection Based on Line Segments Dongwook Kim 1, Liu Zheng Dept. of Information & Communication Eng., Jeonju Univ. Abstract. In this paper, a new car license plate detection method based on line-segmenting is proposed. We introduce a local line-segmenting method,which is independently performed for the edges of horizontal and vertical direction, respectively. Next, we introduce the suitability check method. The proposed method can accurately detect the slightly inclined license plate. Keywords: License Plate Detection, Edge Detection, Image Processing. 1 Introduction Generally, car license number recognition technology has three steps, which are the detection of local license plate, the separation of each character or digit from the detected license plate, and the recognition of the included characters or digits from separated region. This paper is a study about license plate region detection, the first step, among three steps. Since the result of the License plate region detection affects the next steps, accurate detection is required. Conventional studies of license plate region detection can be divided into color based methods and brightness based methods [1]. Our study is about the brightness based method uses edges of input image. Since the license plate generally has a rectangular shape with a known aspect ratio, it can be extracted by finding all possible rectangles in a vehicle image [2]. In order to detect edges, several operators are used, such as Sobel operator [3][4][5]. In this paper, in order to detect a plate, we introduce a new plate detection method based on line-segmenting. 1 Corresponding author, dwkim@jj.ac.kr ISSN: ASTL Copyright 2014 SERSC

2 2 The proposed algorithm Fig.1. The step of the propose algorithm Fig. 1 represents the steps of proposed algorithm. First step is edge detection that is performed for horizontal and vertical direction separately. It is because a license plate is generally rectangular-shaped. Two boundaries, thoseare the up and down of the rectangular, are mostly composed with horizontal edges, the left and right boundaries with vertical edges. In order to get edges, Sobel operator is used in this paper. The remainder of our algorithm is as follows. Binary connected component labeling is widely used in the fields of the image processing and the computer vision. Edge simplification is based on the connected component labeling method, which assigns the same label to the connected components, pixels. If the length of the connected components is shorter than a given threshold, the components get removed. In Fig. 2, the length of Segment-A and B is shorter than a given threshold, Segment-A and B must be eliminated. On the other hand, Segment-C is not deleted because it is longer than the threshold. This process is applied to every connected component in the edge image. In this paper, we call this process as the edge simplification. Remaining components that are not deleted by the edge simplification are used in generating of line segments.we assign a line segment to the connected components having the same label. Fig. 3 illustrates line segments. 100 Copyright 2014 SERSC

3 Fig.2. Connected component labeling (a) Edge image (b) Edge simplification (c) Line segments Fig. 3. Edge simplification and line segmenting Now, we should determine the boundary of the license plate region. There are some considerations in selecting of candidate plate region. In this paper, we consider the ration of the height between two horizontal lines and the width between two vertical lines as the most important thing. In addition, the minimum height and width are used.the suitability check determines whether a candidate region selected meets different features of car license plate or not. 3 Simulation Results In order to demonstrate performance of the proposed technique, simulations were done with several images of size. Several figures contained in Fig. 4 show the results performed by the proposed algorithm. Fig. 4(c) and (f) represent horizontal and vertical edges obtained by the simplification process, respectively. Now, line segments can be found on the simplified edges obtained in the former. Fig. 4(d) and (g) show line segments of horizontal and vertical directions, respectively. By combining Fig 4(d) and (g), we can get the result of Fig.4(h), which contains all of horizontal and vertical components. Fig. 4(i) is a rectangular constituted with 4-line segments and Fig. 4(j) represents the plate region extracted by the rectangular. Copyright 2014 SERSC 101

4 Simulation results show that the proposed algorithm can exactly detect the plate tilted slightly. Fig. 4. The results by the proposed method 4 Conclusions In this paper, a new car license plate detection method based on line-segmenting is proposed. Using a local line-segmenting method, the candidate segments of a rectangular which composes the license plate detected. We also introduced the suitability check method which is based on the horizontal and vertical proportion of line segments and statistical characteristics of the given region. The proposed method 102 Copyright 2014 SERSC

5 can accurately detect the slightly inclined license plate, and also it is more robust than the conventional detection methods based on edge. References 1. C.-N. E. Anagnostopoulos, I. E. Anagnostopoulos, I. D. Psoroulas, V. Loumos, and E. Kayafas. License plate recognition from still images and video sequences: A survey, IEEE Trans. Intell. Transp. Syst., 9, 3, pp (2008) 2. Shan Du, et al., Automatic License Plate Recognition (ALPR): A State-of-the-Art Review, IEEE Trans. on Circuits and Systems for video technology, 23, 2, pp (2013) 3. D. Zheng, Y. Zhao, and J. Wang, An efficient method of license plate location, Pattern Recognit. Lett., 26, 15, pp (2005) 4. S. Wang and H. Lee, Detection and recognition of license plate characters with different appearances, in Proc. Int. Conf. Intell. Transp. Syst., 2. pp (2003) 5. Rongbao and YunfeiLuo, An improved license plate location method based on edge detection, in Proc. International Conference on Applied Physics and Industrial Engineering pp (2012) Copyright 2014 SERSC 103