Application Research On Image Segmentation Based On Wavelet Transform And License Plate Recognition Problems

Image segmentation is thoroughly active research domain in the field of computer image recognition and comprehension. It's the basic of image comprehension. Activate contour model is a important method of image segmentation, and can segment the object accurately, so it has already become an important research field. Wavelet transform is a powerful tool in the signal and image processing, and its fundamental theory has been formed. Wavelet transform has many properties which other signal analysis techniques (for example, Fourier analysis, Gabor Transform, etc) do not have. Because of the multiresolution property, the wavelet transform provides image's characters on different channel and different scale.This paper generalizes the gradient vector flow and then introduces an improved external force based on dyadic wavelet transform. The detail coefficients of image wavelet transform are used to derive the new external force, so the snake can track the object contours through the multi-scale space of an image. In additional, aimed at the snake's dependence on initial contour points, one-dimensional maximum-entropy threshold algorithm is adopted to segment the image firstly and then obtain the initial contour points, which reduce the manual operation as well as improve the convergence of snake speed. Experimental results proved that the new model can greatly get rid of influence of noise and search concave contours. Furthermore, it is efficiently convergence to weak boundary.With the development of information technology and intelligence technology, the informatization and intelligentizing of traffic management is the trend. License plate recognition system (LPR) is the core of intelligent traffic system (ITS). It is very important in modern traffic management systems. In recent years, the study on the critical techniques for LPR has already become an important research field of scientific circles.In this paper we discuss the main parts of LPR: license plate location, slant correction and character segmentation, and make a deep research on some important and key technology. Automatic vehicle location license plate is the basic of LPR. It's difficult for realizing this technology in complex background and complex environment. According to a great deal of horizontal texture of vehicle image, some preprocesses such as adaptive binary conversion, a series of morphological operations which can greatly decrease the noise and useless information in vehicle image; then the method of region analysis can select some candidate regions; lastly using prior knowledge locate the license plate region accurately. Next step is the characters segmentation. We can get the corners of the license image using the Harris algorithm. At the same time, the slant angle of license plate is necessary to use the method combined with Hough transform and corner information. Then we excise the border of the characters and segment the characters. Based on the experiments dealing with images taken under various real world conditions, the results prove that this proposed method can relatively locate license plate and segment characters. It shows that the performance of the system is promising, robust and timely.