Real-time object detection using matlab and webcam / Abdul Azim Mohamad Roseli
Webcam is normally used for live video for conference calls or uploading the image to the social network. It consists of capturing and recording images. However, the use of webcam is seldom used for recognition of an object. In this project, a USB Webcam are considered as Close Circuit Television (C...
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2016
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Online Access: | https://ir.uitm.edu.my/id/eprint/98708/1/98708.pdf |
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my-uitm-ir.987082024-11-26T07:00:33Z Real-time object detection using matlab and webcam / Abdul Azim Mohamad Roseli 2016 Mohamad Roseli, Abdul Azim Image processing Electric apparatus and materials. Electric circuits. Electric networks Webcam is normally used for live video for conference calls or uploading the image to the social network. It consists of capturing and recording images. However, the use of webcam is seldom used for recognition of an object. In this project, a USB Webcam are considered as Close Circuit Television (CCTV) and the objectives of this work is to help a person to detect and monitor their safety as the USB Webcam act as a CCTV. The scope of study of this project is to identify and differentiate the type of object from the USB Webcam. MATLAB programing is utilized to interface the webcam with the MATLAB software to encoded and distinguish the type of an object. A USB webcam are employed to differentiate and capture the object movement. The functionality of the hardware and software are tested when there is movement as the camera captured the images. The result of this project is that a person can acknowledge the object ahead either it is a humans or an animal. 2016 Thesis https://ir.uitm.edu.my/id/eprint/98708/ https://ir.uitm.edu.my/id/eprint/98708/1/98708.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Sulaiman, Suhana |
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Universiti Teknologi MARA |
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UiTM Institutional Repository |
language |
English |
advisor |
Sulaiman, Suhana |
topic |
Image processing Image processing |
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Image processing Image processing Mohamad Roseli, Abdul Azim Real-time object detection using matlab and webcam / Abdul Azim Mohamad Roseli |
description |
Webcam is normally used for live video for conference calls or uploading the image to the social network. It consists of capturing and recording images. However, the use of webcam is seldom used for recognition of an object. In this project, a USB Webcam are considered as Close Circuit Television (CCTV) and the objectives of this work is to help a person to detect and monitor their safety as the USB Webcam act as a CCTV. The scope of study of this project is to identify and differentiate the type of object from the USB Webcam. MATLAB programing is utilized to interface the webcam with the MATLAB software to encoded and distinguish the type of an object. A USB webcam are employed to differentiate and capture the object movement. The functionality of the hardware and software are tested when there is movement as the camera captured the images. The result of this project is that a person can acknowledge the object ahead either it is a humans or an animal. |
format |
Thesis |
qualification_level |
Bachelor degree |
author |
Mohamad Roseli, Abdul Azim |
author_facet |
Mohamad Roseli, Abdul Azim |
author_sort |
Mohamad Roseli, Abdul Azim |
title |
Real-time object detection using matlab and webcam / Abdul Azim Mohamad Roseli |
title_short |
Real-time object detection using matlab and webcam / Abdul Azim Mohamad Roseli |
title_full |
Real-time object detection using matlab and webcam / Abdul Azim Mohamad Roseli |
title_fullStr |
Real-time object detection using matlab and webcam / Abdul Azim Mohamad Roseli |
title_full_unstemmed |
Real-time object detection using matlab and webcam / Abdul Azim Mohamad Roseli |
title_sort |
real-time object detection using matlab and webcam / abdul azim mohamad roseli |
granting_institution |
Universiti Teknologi MARA (UiTM) |
granting_department |
Faculty of Electrical Engineering |
publishDate |
2016 |
url |
https://ir.uitm.edu.my/id/eprint/98708/1/98708.pdf |
_version_ |
1818587993976340480 |