| Summary: | 碩士 === 國立臺灣科技大學 === 電子工程系 === 101 === Lane-mark detection is one of the most important parts in intelligent transportation systems (ITS). We use the camera mounted front of vehicle to capture the road scene for detecting lane-marks. The proposed methods consist of six parts. In the first part, we determine the region of interest (ROI) of captured image and apply the Canny edge detector to investigate boundaries. In the second part, we divide the boundary image into sub-images to calculate local edge-orientation of each block and remove the edge with abnormal orientation. In the third part, we propose the edge-pair scanning method to verify the edges which belong to lane-marks by using the relationship of adjacent edges of lane-marks and the width between these two edges. In the fourth part, we also divide the image into sub-images and apply the feature that road lane-marks are always painted with high contrast colors with the road surface. Then, we use multi-adaptive thresholding method for each block. In the fifth part, we develop the mechanisms of verification and treatments for these candidate lane-mark edges. In the sixth part, we calculate the lane-marks as straight line and curve line models and apply Kalman filter to track it. In the experiment, the proposed system is evaluated in several situations such as bad weather conditions, shadow effect, or road sign on the road. The results show that the proposed method can detect the lane-marks in real-time for various different environments.
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