Video surveillance and monitoring system
Also available in printed version
| Main Author: | |
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| Other Authors: | |
| Format: | Bachelor thesis |
| Language: | English |
| Published: |
Universiti Teknologi Malaysia
2025
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| Online Access: | https://utmik.utm.my/handle/123456789/59613 |
| Abstract | Abstract here |
| _version_ | 1854975138808725504 |
|---|---|
| author | Ng, Chin Haur |
| author2 | Johari Halim Shah Osman, supervisor |
| author_facet | Johari Halim Shah Osman, supervisor Ng, Chin Haur |
| author_sort | Ng, Chin Haur |
| description | Also available in printed version |
| format | Bachelor thesis |
| id | utm-123456789-59613 |
| institution | Universiti Teknologi Malaysia |
| language | English |
| publishDate | 2025 |
| publisher | Universiti Teknologi Malaysia |
| record_format | dspace |
| record_pdf | Abstract |
| spelling | utm-123456789-596132025-03-17T19:03:48Z Video surveillance and monitoring system Ng, Chin Haur Johari Halim Shah Osman, supervisor Electrical engineering Also available in printed version Video surveillance and monitoring system has been an important tool for crime prevention as well as a method of facilitating post-event investigation. However, recent trend has sees the developments of "Intelligent Close Circuit television (CCTV)". These systems are now possible to identify suspicious behavior and lock onto potential suspects. Such technology could help prevent invasion from the intruders by spotting odd elements in a situation and warn user about the possible intrusion. The main objective of this project is to create a video surveillance and monitoring system which is able to autonomously detect human, capture the image of intruder and trigger alarm to alert user whenever certain threshold parameter are exceeded. The major algorithm proposed to implement the face detection feature is by applying Haar-like feature frontal face detection. This method runs through trained database to match the 3000 probability of faces with the target faces in a video sequence. However, this solution is only effective when the target faces is not tilting or bending to one side. In fact, looping of program which requires program iteration to run through database for face matching could be time consuming too. Moreover, a two degree of freedom (2 d.o.f.) pan and tilt mechanical structure is included in the system to widen the angle of viewing of the system. Incorporation of this feature had caused the camera not to be stationary. Therefore, it is required to stabilize the moving camera. A rapid and robust human detection and tracking algorithm called Continuously Adaptive Mean Shift algorithm is incorporated in order to solve the problems. This algorithm uses combination of colors information rather than relying to a single color. Since it tracks by color, a face with orientation changes can be followed smoothly thus showing great robustness in scenarios of crowded, background distraction and partial occlusions atiff UTM 76 p. Project Paper (Sarjana Muda Kejuruteraan (Elektrik - Mekatronik)) - Universiti Teknologi Malaysia, 2011 2025-03-17T06:09:21Z 2025-03-17T06:09:21Z 2011 Bachelor thesis https://utmik.utm.my/handle/123456789/59613 valet-20170411-14593 vital:98050 ENG Closed Access UTM Complete Unpublished application/pdf Universiti Teknologi Malaysia |
| spellingShingle | Electrical engineering Ng, Chin Haur Video surveillance and monitoring system |
| thesis_level | Other |
| title | Video surveillance and monitoring system |
| title_full | Video surveillance and monitoring system |
| title_fullStr | Video surveillance and monitoring system |
| title_full_unstemmed | Video surveillance and monitoring system |
| title_short | Video surveillance and monitoring system |
| title_sort | video surveillance and monitoring system |
| topic | Electrical engineering |
| url | https://utmik.utm.my/handle/123456789/59613 |
| work_keys_str_mv | AT ngchinhaur videosurveillanceandmonitoringsystem |