車道線偵測與追蹤方法

專利類型

發明

專利國別 (專利申請國家)

中華民國

專利申請案號

108119544

專利證號

I 694019

專利獲證名稱

車道線偵測與追蹤方法

專利所屬機關 (申請機關)

國立中正大學

獲證日期

2020/05/21

技術說明

我們提出一個有系統的演算法，其演算法整合全卷積神經網路(fully convolutional network，FCN)與機率圖模型(probabilistic graphical model)，分別用於車道線偵測和追蹤。此演算法主要分成三個部分：候選車道線提取、多成分車道線建模和多成分車道線追蹤，車道線提取步驟透過結合傳統影像處理提取的低階車道線邊緣與FCN提取的高階車道線段偵測候選車道線，候選車道線被偵測與分群後，使每條車道線分成n個成分，並將車道線成分加上整條車道線作為霍夫轉換域中的節點，換而言之，我們透過具有n+1個節點的連結架構為每條車道線建模。最後，建立機率圖模型同時追蹤霍夫域中的多條車道線。實驗結果顯示，我們的方法可以追蹤典型城市場景中各種具有挑戰性情況下的車道線，例如：彎道、紋理標記和車道線遮蔽。 We proposed a systematic algorithm that integrates a fully convolutional network (FCN) for lane detection and a probabilistic graphical model for lane tracking. The proposed method consists of three main steps: lane candidate extraction, multi-component lane modeling and multi-component lane tracking. The lane extraction step detects land candidates by fusing low-level lane edges extracted by traditional image processing and high-level lane segments extracted by the designed FCN. After lane candidates are detected and clustered, we divide each lane into n components and represent lane components plus whole lanes as nodes in the Hough transform domain. That is, we model each lane by a link structure with n+1 nodes. Finally, a probabilistic graphical model is built to track multiple lanes through frames in the Hough domain at the same time. The experimental results show that our method can track lanes in various challenging conditions in typical urban scenes such as curved lanes, texture marking, and lane occlusion.

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