以視覺為基礎的車對車偵測及追蹤系統; A Vision-based Vehicle to Vehicle Detection and Tracking System

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/8983

Title:	以視覺為基礎的車對車偵測及追蹤系統;A Vision-based Vehicle to Vehicle Detection and Tracking System
Authors:	黃宇辰;Yu-Chen Huang
Contributors:	資訊工程研究所
Keywords:	智慧型運輸系統;前車追蹤;前車偵測;Vehicle tracking;Vehicle detection;ITS
Date:	2005-06-23
Issue Date:	2009-09-22 11:38:50 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	近幾年來，人民生活素質提昇，對於行的安全越加重視，因此車輛安全駕駛的研究也變得越重要。為了車輛輔助安全駕駛，我們將一部相機架設在車上，用來偵測及追蹤前車，並與其他系統整合，分析行車狀況。我們所提出的前車追蹤系統共分為兩個狀態 : 偵測與追蹤狀態。在偵測狀態中，我們利用水平邊及車子底下陰影來偵測可能的前車位置，然後使用垂直邊和對稱性來偵測前車。之後，再以一個最小矩形框來代表我們所找到的前車區塊。最後再利用車寬和車道寬的比例、對稱性、及區塊色彩標準差來驗證是否為前車區塊。在追蹤狀態，我們先預測前車位置，然後在預測位置的附近再去做搜尋，找到前車區塊後，我們利用車寬與車道寬的比例、對稱性、區塊色彩標準差、及透視投影的觀念來驗證是否為車輛；若是車輛，則比對是否為之前所找到的車輛，如果比對成功，則更新前車區塊。我們以多種的天候狀況影像 ; 例如，晴天、陰天、多雲、和雨天等，來測試我們的系統。從實驗的結果顯示，我們所提出的系統可以在不同的天候狀況下，即時地偵測及追蹤前車。 In the recent years, the study on safe driving becomes more and more important. To aid the safe driving, we use a camera mounted on a vehicle to capture road scenes for detecting preceding vehicles. The proposed system consists of three parts. In the first part, we use horizontal edge and underneath shadow of a possible preceding vehicle to locate the vehicle. We then use the vertical edge and symmetry property to detect the vehicle. Finally, we represent the possible vehicle by a detected box. In the second part, we use the lane width, vehicle width, symmetry, and color variance of pixels in the detected box to verify the vehicle. In the third part, we track and search vehicles in a narrow area. The first and third parts are independently executed following by the second part. That is we detect or track a preceding vehicle based on the current situation, then verify the detected or tracked objects. In the experiments, the proposed detector is evaluated on several different weather conditions such as sunny day, misty day, dusky day, cloudy day, and rainy day. From the experimental results, we find that the proposed approach can robustly and accurately detect or track the preceding vehicles in real time.
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

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