本文選題：垂直投影校正 + 加權投票��； 參考：《南京理工大學》2017年碩士論文

【摘要】：可通行區(qū)域檢測是智能車輛視覺技術的關鍵技術之一,廣泛應用于智能交通系統(tǒng)、車輛輔助駕駛系統(tǒng)等領域。基于單一的圖像,本文從消失點、障礙物和道路分割三個方面研究了智能車輛在非結構化道路上的可通行區(qū)域檢測方法。首先,針對彎曲道路消失點檢測不準確的問題,本文提出了一種新的基于加權投票的消失點檢測方法。該方法先用垂直投影校正方法來校正投票點的Gabor紋理主方向,再通過投票點對上方的、位于同一條邊緣線上的其他投票點進行加權的方法計算出投票權值,最后用該權值進行加權投票,以檢測出消失點。消失點檢測實驗驗證了本文方法檢測效果最好,并且可以滿足系統(tǒng)實時性要求。其次,基于樹木、欄桿等障礙物都有一定豎直結構的事實,本文提出了一種新的基于Haar-like特征和紋理主方向的豎直障礙物檢測方法。該方法先使用線性矩形特征區(qū)分出障礙物與背景,再通過在矩形區(qū)域內垂直紋理概率多少來判別該矩形是否包含障礙物。后面的障礙物檢測實驗表明,該方法可以準確檢測出豎直障礙物,并且障礙物矩形內投票點進行逆投票,可以消除障礙物對消失點檢測的干擾。最后,為了提高彎曲道路分割的準確度,本文提出了基于消失點的分段道路分割方法。該方法先將圖像在消失點以下的區(qū)域按高度比例分為兩部分,再基于真實道路在圖像中的形狀情況,一一計算邊界。道路分割實驗驗證了本文方法滿足系統(tǒng)實時性的要求,并且提高了道路分割的準確度。
[Abstract]:The detection of passable area is one of the key technologies of intelligent vehicle vision technology. It is widely used in the fields of intelligent transportation system and vehicle assisted driving system. Based on a single image, this paper studies the method of detecting the passable area of intelligent vehicle on unstructured road from three aspects: vanishing point, obstacle and road segmentation. Firstly, a new vanishing point detection method based on weighted voting is proposed to solve the problem of inaccurate detection of vanishing points in curved roads. This method uses the vertical projection correction method to correct the main direction of the Gabor texture of the polling point, and then calculates the voting value by weighting the other polling points located on the same edge line above the polling point. Finally, weighted voting with the weight value is used to detect the vanishing point. The experiment of vanishing point detection shows that the proposed method has the best detection effect and can meet the real-time requirement of the system. Secondly, based on the fact that obstacles such as trees and railings have a certain vertical structure, a new method of vertical obstacle detection based on Haar-like features and texture principal direction is proposed in this paper. The method first uses linear rectangular features to distinguish obstacles from backgrounds, and then determines whether the rectangle contains obstacles by the probability of vertical texture in the rectangular region. The experiment of obstacle detection behind shows that the method can accurately detect vertical obstacles and reverse vote at polling points in the rectangle of obstacles, which can eliminate the interference of obstacles to detection of vanishing points. Finally, in order to improve the accuracy of curved road segmentation, a segmented road segmentation method based on vanishing points is proposed. In this method, the region below the vanishing point is divided into two parts according to the height, and then the boundary is calculated one by one based on the shape of the real road in the image. Road segmentation experiments show that the proposed method meets the real-time requirements of the system and improves the accuracy of road segmentation.
【學位授予單位】：南京理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U463.6;TP391.41

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