The Research of Applying Image Processing Technology to Detect and Track Vehicles on Highway

碩士 === 國立彰化師範大學 === 電機工程學系 === 101 === This thesis proposes the application of image processing technology in the vehicle detection system, which can automatically retrieve traffic information from the monitor on highway. The process can be divided into vehicle detection and vehicle tracking. Its ma...

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Main Author: 趙冠維
Other Authors: 鍾翼能
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/67979685638275407794
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spelling ndltd-TW-101NCUE54420582016-03-16T04:15:03Z http://ndltd.ncl.edu.tw/handle/67979685638275407794 The Research of Applying Image Processing Technology to Detect and Track Vehicles on Highway 應用影像處理技術於公路車輛偵測及追蹤之研究 趙冠維 碩士 國立彰化師範大學 電機工程學系 101 This thesis proposes the application of image processing technology in the vehicle detection system, which can automatically retrieve traffic information from the monitor on highway. The process can be divided into vehicle detection and vehicle tracking. Its main purpose is to collect traffic parameters, and to achieve the traffic management. In the vehicle detection, the system uses a series of image processing methods to obtain vehicle targets. The shadow will be removed based on the threshold in the HSV color space. All detection processes are set in the region of interest, so that computational complexity can be reduced to improve execution speed. In the vehicle tacking procedure, we use feature extraction method to obtain the bounding box of the vehicle. This thesis uses the bounding box boundary length and area to complete the vehicle size classification, and uses the virtual detection line to calculate the vehicle counting. We can get vehicle speed by calculating the frames it takes when vehicles pass the sensing area. As shown in the experiments, the proposed method can provide accurate traffic information and be helpful to the traffic management. 鍾翼能 2013 學位論文 ; thesis 61 zh-TW
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description 碩士 === 國立彰化師範大學 === 電機工程學系 === 101 === This thesis proposes the application of image processing technology in the vehicle detection system, which can automatically retrieve traffic information from the monitor on highway. The process can be divided into vehicle detection and vehicle tracking. Its main purpose is to collect traffic parameters, and to achieve the traffic management. In the vehicle detection, the system uses a series of image processing methods to obtain vehicle targets. The shadow will be removed based on the threshold in the HSV color space. All detection processes are set in the region of interest, so that computational complexity can be reduced to improve execution speed. In the vehicle tacking procedure, we use feature extraction method to obtain the bounding box of the vehicle. This thesis uses the bounding box boundary length and area to complete the vehicle size classification, and uses the virtual detection line to calculate the vehicle counting. We can get vehicle speed by calculating the frames it takes when vehicles pass the sensing area. As shown in the experiments, the proposed method can provide accurate traffic information and be helpful to the traffic management.
author2 鍾翼能
author_facet 鍾翼能
趙冠維
author 趙冠維
spellingShingle 趙冠維
The Research of Applying Image Processing Technology to Detect and Track Vehicles on Highway
author_sort 趙冠維
title The Research of Applying Image Processing Technology to Detect and Track Vehicles on Highway
title_short The Research of Applying Image Processing Technology to Detect and Track Vehicles on Highway
title_full The Research of Applying Image Processing Technology to Detect and Track Vehicles on Highway
title_fullStr The Research of Applying Image Processing Technology to Detect and Track Vehicles on Highway
title_full_unstemmed The Research of Applying Image Processing Technology to Detect and Track Vehicles on Highway
title_sort research of applying image processing technology to detect and track vehicles on highway
publishDate 2013
url http://ndltd.ncl.edu.tw/handle/67979685638275407794
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