Paper
8 January 1999 Vision-based object detection and recognition system for intelligent vehicles
Bin Ran, Henry Xianghong Liu, Wilfung Martono
Author Affiliations +
Proceedings Volume 3525, Mobile Robots XIII and Intelligent Transportation Systems; (1999) https://doi.org/10.1117/12.335712
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States
Abstract
Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bin Ran, Henry Xianghong Liu, and Wilfung Martono "Vision-based object detection and recognition system for intelligent vehicles", Proc. SPIE 3525, Mobile Robots XIII and Intelligent Transportation Systems, (8 January 1999); https://doi.org/10.1117/12.335712
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Visual process modeling

Neural networks

Object recognition

Data modeling

Image analysis

RGB color model

Intelligence systems

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