Racing car detection using cascaded classifier / Ho Seck Wei

Ho, Seck Wei (2017) Racing car detection using cascaded classifier / Ho Seck Wei. Masters thesis, University of Malaya.

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    Human error tends to occur especially when it comes to recognizing or detecting an object, the situation becomes worst when human has made the wrong judgement due to poor observation skills, causing a side effect to what happens subsequently. To minimize these wrong judgement, machine learning is proposed to assist them via detection and classification. Machine vision system is one of the technology where it will be a great useful application in the near future for it will enable a system to analyze and communicate with other devices to run its respective task. The general concept of how a machine vision system works is fully based on the fundamental of image processing, therefore the main requirement for a machine vision system is combination of both hardware and software to execute its task. This study is performed to detect racing cars from any sources that are obtained with a robust, stable and high efficiency.

    Item Type: Thesis (Masters)
    Additional Information: Thesis (M.A.) - Faculty of Engineering, University of Malaya, 2017.
    Uncontrolled Keywords: Human error; Machine vision system; Machine learning; Image processing
    Subjects: T Technology > T Technology (General)
    T Technology > TK Electrical engineering. Electronics Nuclear engineering
    Divisions: Faculty of Engineering
    Depositing User: Mr Prabhakaran Balachandran
    Date Deposited: 27 Oct 2017 11:33
    Last Modified: 03 Jun 2020 03:38

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