Model-Based Robust Lane Detection for Driver Assistance

Abstract

In this paper, we propose an efficient and robust lane detection method for detecting immediate left and right lane boundaries of the lane in the roads. The proposed method are based on hyperbolic lane model and the reliable line segment clustering. The reliable line segment cluster is determined from the most probable cluster obtained from clustering line segments extracted by the efficient LSD algorithm.Experiments show that the proposed method works robustly against lanes with difficult environments such as ones with occlusions or with cast shadows in addition to ones with dashed lane marks, and that the proposed method performs better compared with other lane detection methods on an CMU/VASC lane dataset.

Design and Implementation of Autonomous Car using Raspberry Pi

“…Thus the region of interest is defined from the nearest region to the farther distances by moving upwards in the image created. The height of the region of interest is usually not more than half the height of image [23]. This removes the sky area from the visual field and saves unnecessary computations and is better than the method proposed by H.Dahlkamp [3].…”

Video Oyunu Ortamında Otonom Sürüş İçin Şerit Tespiti

“…Classical methods mainly consist of detecting edges or matching them to predefined templates. These methods introduce noise into the extracted lane information (Duong et al, 2014). Using CNNs for lane detection has several advantages over traditional methods.…”

Preprocessing Technique for Lane Detection Using Image Clustering and HSV Color Model

“…비전 센서를 이용한 차선 검출을 위하여 여러 가 지 전처리 방법이 사용되고 있는데 [6][7][8][9][10], 대표적으 로 차선 윤곽선을 뽑을 수 있는 에지 검출기(edge detector) [6,8], 적응형 히스토그램(adaptive histogram) 방법 [9], 모폴로지(morphology) 방법 [ …”