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.
Extraction of the license plate region is challenging first step in the license plate recognition system. The paper proposed approach is not only simple but also more effective than some of the existing method earlier. A new dynamic RGB threshold formula by limiting the hue change range is educed. The license image is made grids. Then we can plot and mark them by the formula and operate them with...
License plate location is one of the key link in the license plate recognition process. Whether the plate location is successful and how accurate is the location decide directly the recognition and the effects in the latter part. For the license plate area has a high density difference in the difference image,we have put forward an algorithm for the license plate location based on the density and...
License plate recognition system (LPRS) is the hard core of the intelligent traffic system. In this paper, license plate (LP) frame was captured from video image sequences by background-difference, and an improved Kalman filter method was adopted to update the background. By means of mathematical morphology (MM) and edge characteristic analysis, LP orientation was conducted. After the binarization...
A shadow detection algorithm base on spatial features was proposed, in the case of focusing on traffic vehicle detection system. First of all, multi-foreground rectangles were extracted by using Gaussian mixture model (GMM) and edge detection operator of mathematical morphology. Then, histogram of horizontal location - foreground point number of vertical direction was computed, combined with optimum...
An algorithm for moving vehicles localisation in digital image sequences is presented and initially explored. It can be in future applied e.g. as a step in traffic monitoring, speed verification, accident detection, searching for stolen cars, license plates recognition, etc. It is based on selection of sections, that are different from background in consecutive frames. It requires earlier preparation...
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.