Image-based Vehicle Rear Warning System

Image-based Vehicle Rear Warning System

碩士 === 元智大學 === 電機工程學系 === 104 === This paper develops a Image-based Vehicle Rear Warning System, the Image-based Vehicle Rear Warning System consists of three main components: lane image tracking, vehicle image recognition and blind spot detection. Lane image tracing to lane Hough Transform find im...

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Main Authors: Chen-Yi Tsou, 鄒振益
Other Authors: Wen-Hsing Kuo
Format: Others
Language:zh-TW
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/91810536268222896676
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spelling ndltd-TW-104YZU054420082017-10-15T04:36:57Z http://ndltd.ncl.edu.tw/handle/91810536268222896676 Image-based Vehicle Rear Warning System 影像為基礎之車輛後方警示系統 Chen-Yi Tsou 鄒振益 碩士 元智大學 電機工程學系 104 This paper develops a Image-based Vehicle Rear Warning System, the Image-based Vehicle Rear Warning System consists of three main components: lane image tracking, vehicle image recognition and blind spot detection. Lane image tracing to lane Hough Transform find images; Vehicle image recognition aspect of the vehicle to AdaBoost training Haar-like features into a strong classifier, reached after vehicle image quickly identify with Cascade classifiers architecture; blind spot detection, after the vehicle image enter the set warning distance, determining the distance between the front and rear of the vehicle. In image processing, image processing using OpenCV library to develop programs, and C / C ++ programming Visual Studio 2010 software under the direct call OpenCV function. Wen-Hsing Kuo Duan-Yu Chen 郭文興 陳敦裕 2016 學位論文 ; thesis 55 zh-TW
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language zh-TW
format Others
sources NDLTD
description 碩士 === 元智大學 === 電機工程學系 === 104 === This paper develops a Image-based Vehicle Rear Warning System, the Image-based Vehicle Rear Warning System consists of three main components: lane image tracking, vehicle image recognition and blind spot detection. Lane image tracing to lane Hough Transform find images; Vehicle image recognition aspect of the vehicle to AdaBoost training Haar-like features into a strong classifier, reached after vehicle image quickly identify with Cascade classifiers architecture; blind spot detection, after the vehicle image enter the set warning distance, determining the distance between the front and rear of the vehicle. In image processing, image processing using OpenCV library to develop programs, and C / C ++ programming Visual Studio 2010 software under the direct call OpenCV function.
author2 Wen-Hsing Kuo
author_facet Wen-Hsing Kuo
Chen-Yi Tsou
鄒振益
author Chen-Yi Tsou
鄒振益
spellingShingle Chen-Yi Tsou
鄒振益
Image-based Vehicle Rear Warning System
author_sort Chen-Yi Tsou
title Image-based Vehicle Rear Warning System
title_short Image-based Vehicle Rear Warning System
title_full Image-based Vehicle Rear Warning System
title_fullStr Image-based Vehicle Rear Warning System
title_full_unstemmed Image-based Vehicle Rear Warning System
title_sort image-based vehicle rear warning system
publishDate 2016
url http://ndltd.ncl.edu.tw/handle/91810536268222896676
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AT zōuzhènyì imagebasedvehiclerearwarningsystem
AT chenyitsou yǐngxiàngwèijīchǔzhīchēliànghòufāngjǐngshìxìtǒng
AT zōuzhènyì yǐngxiàngwèijīchǔzhīchēliànghòufāngjǐngshìxìtǒng
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