• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.545-548
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• 2012

본 논문에서는 영상내 관심영역의 역 투시변환과 차선검출필터를 적용한 실시간 차선검출방법을 제안한다. 영상의 시작 프레임에서 소실점을 찾고 이를 기준으로 관심영역을 설정하고 차선을 예측하였으며, 예측된 차선을 기반으로 역 투시변환계수를 추출하여 원근감이 제거된 영상을 얻고, 이로부터 차선을 검출하였다. 제안한 방법은 원근감이 제거된 영상에 차선검출 필터를 적용하여 차선을 검출하는 방법으로, 처리영역을 축소하고 처리과정을 단순화 함으로써 초당 50 frames 정도의 양호한 차선검출 결과를 보였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2430-2436
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• 2013

This study suggests a method of detecting the still object, which becomes a cause of danger within the crossroad. The Inverse Perspective Transform was performed in order to make the object size consistent by being inputted the real-time image from CCTV that is installed within the crossroad. It established the detection area in the image with the perspective transform and generated the adaptative background image with the use of the moving information on object. The detection of the stop object was detected the candidate region of the stop object by using the background-image differential method. To grasp the appearance of truth on the detected candidate region, a method is proposed that uses the gradient information on image and EHD(Edge Histogram Descriptor). To examine performance of the suggested algorithm, it experimented by storing the images in the commuting time and the daytime through DVR, which is installed on the cross street. As a result of experiment, it could efficiently detect the stop vehicle within the detection region inside the crossroad. The processing speed is shown in 13~18 frame per second according to the area of the detection region, thereby being judged to likely have no problem about the real-time processing.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.304-310
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• 2017

In this paper, we propose the architecture of an IPM based lane detector for autonomous vehicles to detect and control the driving route along the curved lane. In the IPM image, we divide the area into two fields, Far/Near Field, and the lane candidate region is detected using the Hough transform to perform the matching for the curved lane. In autonomous vehicles, various algorithms must be embedded in the system. To reduce the system resources, we proposed a method to minimize the number of memory accesses to the image and various parameters on the external memory. The proposed circuit has 96% lane recognition rate and occupies 16% LUT, 5.9% FF and 29% BRAM in Xilinx XC7Z020. It processes Full-HD image at a rate of 42 fps at a 100 MHz operating clock.