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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Stereovision-Based Object Segmentation for Automotive Applications | EURASIP Journal on Applied Signal Processing 2005 14 2322-2329 2005 Hindawi Publishing Corporation Stereovision-Based Object Segmentation for Automotive Applications Yingping Huang International Automotive Research Center Warwick Manufacture Group University of Warwick Coventry CV4 7AL UK Email yingping.huang@warwick.ac.uk Shan Fu Applied Mathematics Computing Group School of Engineering Cranfield University Bedford MK43 0AL UK Email s.fu@cranfield.ac.uk Chris Thompson Applied Mathematics Computing Group School of Engineering Cranfield University Bedford MK43 0AL UK Email chris.thompson@cranfield.ac.uk Received 14 January 2004 Revised 8 November 2004 Obstacle detection and classification in a complex urban area are highly demanding but desirable for pedestrian protection stop go and enhanced parking aids. The most difficult task for the system is to segment objects from varied and complicated background. In this paper a novel position-based object segmentation method has been proposed to solve this problem. According to the method proposed object segmentation is performed in two steps in depth map X-Z plane and in layered images X-Y planes . The stereovision technique is used to reconstruct image points and generate the depth map. Objects are detected in the depth map. Afterwards the original edge image is separated into different layers based on the distance of detected objects. Segmentation performed in these layered images can be easier and more reliable. It has been proved that the proposed method offers robust detection of potential obstacles and accurate measurement of their location and size. Keywords and phrases stereovision segmentation objects detection. 1. INTRODUCTION Vision-based driver assistance system in complex urban area is highly demanding but desirable for pedestrian protection stop go and enhanced parking aids. The basic requirement for the system is the capability of detecting potential obstacles and providing complete three-dimensional 3D .