The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The license plate location is an essential process in the license plate recognition system, and has been studied widely. In view of vehicles image on different background and light densities, this paper presents a license plate location algorithm based on combinatorial feature. Firstly, we propose to preprocess the image of license plate with traditional but rapid method. Secondly, we define some...
On the basis of the vehicle license plate location, an image grey vertical projection segmentation approach based on the distribution character segmentation is proposed in this paper. A two-stage approach consisting of coarse and accurate segmentation is adopted. It can increase the accuracy of the segmentation and has good segmentation speed. And in recognition process, character features are extracted...
The License plate location is an important stage in Intelligent Transportation System (ITS). It is considered to be the most crucial step of an Automatic License Plate Recognition (ALPR) system. A new image segmentation method based on integrated features and Marker-Controlled Watershed algorithm was proposed to locate and split the plate region of vehicle images from complicated environment. Firstly,...
For the limitation of current license plate location algorithms, present an algorithm of the license plate location based on image energy and its practical formulas. Introduce the algorithm of extraction and methods to verify region of license plate. It takes full advantage of characteristics of the license plate, such as complicated textures, sharp-cut contrast and so on. It also has the advantages...
License plate locating has been the bottleneck of Automatic Vehicle Recognition System. In order to improve the speed and accuracy of license plate locating, this paper proposes a simple and practical method of license plate locating. This method uses the adaboost algorithm to locate license plate. We can first enhance the texture features in the vertical direction of the plate through image preprocessing...
This paper presents a novel approach of license plate location. The proposed algorithm involves the following three steps. First, the vertical edges of the vehicle image are extracted by Sobel operator. Second, HSV color space and integral image are employed to locate candidates in yellow license plates and non-yellow license plates. Finally, connected component analysis is to locate the region of...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.