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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...
We introduce a new computer vision based system for robust traffic sign recognition and tracking. Such a system presents a vital support for driver assistance in an intelligent automotive. Firstly, a color based segmentation method is applied to generate traffic sign candidate regions. Secondly, the HoG features are extracted to encode the detected traffic signs and then generating the feature vector...
This paper presents the performance comparison for lane detection and tracking using two techniques; Hough transform and color thresholding. Hough transform includes the following steps: gray scale conversion, edge detection, Hough space accumulation and un-Hough step to draw line. Color thresholding algorithm comprises color thresholding, morphology filtering and drawing tracking label. The results...
Recently, detection and recognition of traffic panels and their textual information is studied increasingly to become the next working part of driver assistance systems and autonomous cars. These information are especially useful when other facilities fail to provide enough information about routes and places, like when Global Positioning System (GPS) gets blocked in high density urban areas. However,...
Video surveillance has been widely used in many applications. Public safety and theft protections are most important uses of it. A system like this needs an efficient transmission and storage of the large video data. Key frame extraction is a simple and powerful system to accomplish this objective. Keyframe extraction also called as a summary of the video because it gives the only important content...
Traffic sign detection and recognition plays an important role in driver assistance system especially in complexity environment. Firstly, RGB image is converted to standardization image only contained 8 colors for reducing computational burden. Only interesting color components are extracted as candidate region for further recognition. Then HOG descriptor is considered as detection characteristic...
Todays, the number of vehicles is rapidly increasing. In parallel, the number of ways and traffic signs have increased. As a result of increased traffic signs, the drivers are expected to learn all the traffic signs and to pay attention to them while driving. A system that can automatically recognize the traffic signs has been need to reduce traffic accidents and to drive more freely. Traffic sign...
In this paper, we develop a novel method for vehicle classification using color images from surveillance videos. Proposed approach utilizes deformable part based (DPM) object detectors to localize different parts of the vehicle such as license plates and headlights. Next, we extract color features around the detected regions to infer the color of the vehicle. Color descriptors are used to detect the...
As technology advances, it is an urgent matter to develop a smart street light for energy saving and road safety. In this paper, we present a system design of LED street light which integrates multicolor LED, power driving IC, and embedded image processing. The embedded system is used to monitor the road status and output control instruction. As the fog or rain is detected, the embedded system immediately...
This paper presents the last developments towards vision-based target tracking by an AUV. The main concepts behind the visual relative localization are provided and the results from a statistical analysis for the relative localization algorithm are presented. The purpose of this analysis is to ensure properness of data used to feed controllers that are responsible for governing the AUV motion. A new...
This article describes the vertical traffic signs recognition (VTSR) system. In this system the Cambridge optical correlator is used as an image comparator in the recognition stage. In our case, the Cambridge optical correlator compares detected traffic signs with reference traffic signs. One step of the VTSR system is the traffic signs detection process. Traffic signs detection is used to locate...
Dangerous driving behavior is the major factor to cause most of driving accidents. We present a novel method for dangerous driving behavior analysis. When the dangerous driving is detected, the system will issue an alert message to remind driver to pay more attention. The proposed system can detect three kinds of dangerous behavior: dozing, eating, and phoning. Furthermore, since we propose a novel...
The traffic sign detection and recognition is necessary for the safety and proper navigation of drivers. Intelligent driver assistance systems have great potential in emerging technologies. This paper presents an efficient algorithm which detects the traffic sign from video based on colour and shape information. Then the auto associative neural networks are performed to recognise the traffic signs...
Presently, discrete-event dynamic systems represent a significant group of varied systems e.g. computer networks, manufacturing systems, communication systems, database systems etc. An important class of discrete-event systems are automated storage and retrieval systems (AS/RS). There is a big demand for new modelling and control methods of these systems in automotive industry in Slovakia. These systems...
This paper describes the Driver's dashboard implemented in AFV to display important vehicle parameters and a vision system display to perceive the environment for day and night time driving. The dashboard has been designed aesthetically such that it provides real time awareness of the vehicle condition by displaying the critical parameters which requires driver's attention for safe driving while automating...
Traffic signs serve important functions on the road. Drivers can easily determine their directions and vehicle speeds by paying attention to traffic signs. However, it is only natural that sometimes drivers misjudge the position and meaning of traffic signs that they ignore them and in the worst case scenario, got involved in accidents. Therefore, technological improvements allow the development of...
To enhance the robustness of the vehicle detection system, an effective algorithm to identify the lighting conditions (daylight, night, lowlight (dawn, dusk)) based on histogram analysis is presented in this paper. The algorithm consists of two procedures: extracting and updating background image, and generating a lighting conditions classifier based on background image analysis. The algorithm is...
Lane detection is one of the most challenging problems in machine vision and still has not been fully accomplished because of the highly sensitive nature of computer vision methods. Computer vision depends on various ambient factors. External illumination conditions, camera and captured image quality etc. effect machine vision performance. Lane detection faces all these challenges as well as those...
We present a robust real-time vision-based system for vehicle tracking and categorization, developed for traffic flow surveillance. We propose a robust segmentation algorithm that detects foreground pixels corresponding to moving vehicles. Experimental results based on four large datasets show that our method can count and classify vehicles with a high level of performance (more than 98%).
Fast object detection is the most important part of the unmanned surface vehicles (USV) which make it possible for the USV to avoid the obstacle automatically and navigate autonomously. So, it is necessary to find a fast and accurate object detection method. In practice, the significant difficulty is that the environment is quite complicated which make the object uncertain. The obstacle may be a person,...
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