The Research Of Multiple License Plates Localization

The vehicle license plate recognition (LPR) system has a wide application in the automatic tolling system, access control system and traffic monitoring and so on. As an important part of the vehicle license plate recognition, vehicle license plate division (LPD) plays a vital role in the precision of such systems. Present method of LPD focuses mainly on images with single car. Multiple cars appearing in the same image is more common in the real world. What's more, the vehicle image is most likely with complex scenes as well. To deal with vehicle license plates division in such situations, images with multiple cars in complex scenes are studied in this paper. The image processing technology proposed in this paper can divide the area in which the car plate is located as close as possible. The experimental results show that multiple car plates within the same image in complex scenes can be separated correctly and accurately.In this paper, current research status and application of LPR are introduced, the developing and defect about LPD are discussed first. Then the key techniques including edge detection, component connectivity analysis, slant correction etc. manifold methods, multiple vehicle license plates location and division are expatiated. The main contributions of this paper are summarized as follows:1. Several pre-processing methods of image processing are adopted. Including conversion from colored-images into gray-scale images, gray balance and eliminate the differences between images caused by illumination. The pre-processing makes the contrast of images more significant, so the stroke characteristics of license number in the region stand out. The wavelet transform using threshold settings partial approach is introduced to de-noise the image as the last step in pre-processing stage.2. After the pre-processing stage, mathematical morphology method is used to deal with the images which containing several license plates. The suspected locations of license plate are isolated into different simply connected domain. In order to extract of images which contain various type of edges, the morphology of computing is combined with set computing in this paper. And multiple structure elements of morphology are used to detect the edges of connected domain. During our experiment we found that the result we get by using multiple structure elements of the image edge detection operator of morphological during the dilation and erosion is much better than that we get by using the traditional edge detection methods. After the edge detection, a variety of morphological image processing operations are used to determine the connectivity of the suspected domains.3. Then, in order to detect the suspected license plates more accurately, a reformed Hough transform was proposed in this paper to correct the tilt of connected domain.4. Finally by using of license plate information of the characteristics of a single plate of the suspected area of the false certification, license plates achieve accurate positioning. Experimental results show that the complexity of the proposed algorithm is low for many of the license plate image segmentation. It can meet the fast, accurate positioning requirements for LPD system. What's more is that this algorithm has pretty good robustness due to this algorithm not very sensitive to most of the context of complex, uneven lighting, low contrast characters and background, as well as distribution vehicles.