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.
Road marking is a key visual cue for driving in structured environments like highways and urban roads. Road marking detection plays an important role in advanced driver assistant systems and autonomous driving. Robust road marking detection is challenging for the variation of road scenes, the degradation of the markings and the changes of the illumination. Traditional algorithms mainly use the grayscale...
Lane detection is a critical step in advanced driver assistance systems (ADAS). The detected lane information is used by later modules of warning and controlling the differential brake and steering angle. Here we propose an efficient algorithm for detecting accurate lane inbounds under varying illumination and road conditions like curvy, straight and dashed lane markings, deterministically. The current...
Modern amenities, fast data transfer and minimum delay have now become the basic requirements of all the services. This has now come in a large way in transport services also. One such service offered to transport system is toll collection. Initially toll collection was manual but now due to development in various fields it is slowly moving towards automation. The system discussed in this paper is...
Obstacle detection is a fundamental task for Advanced Driver Assistance Systems (ADAS) and Self-driving cars. Several commercial systems like Adaptive Cruise Controls and Collision Warning Systems depend on them to notify the driver about a risky situation. Several approaches have been presented in the literature in the last years. However, most of them are limited to specific scenarios and restricted...
Pedestrian detection is an important research field in advanced driver assistance system (ADAS). This paper puts forward a pedestrian detection framework based on both heuristic statistics and machine learning. First, a restriction of region of interest (ROI) is set on the captured image. Second, the template matching coarsely detects candidate pedestrians by using a set of template images, the edge...
In this paper, we propose novel block-based techniques for robust extraction of lane marking edges in complex scenarios, such as in the presence of shadows, vehicles, other road markings etc. The techniques are based on the properties of lane markings and involve a two-stage processing: (1) generation of customized edge maps using histograms of gradient angles, and (2) directional signed edges in...
This paper proposes an effective lane detection and tracking method using statistical modeling of lane color and edge-orientation in the image sequence. At first, we will address some problem of classifying a pixel into two classes(lane or background) and detecting one exact lane. Generally, the probability of a pixel classification error conditioned on the distinctive feature vector can be decreased...
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.