Zalida Wati Ahmad creator text theses my Kuantan, Pahang UMP 2012 monographic eng

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x, 44 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM In computer vision field, head detection can be considered as one of the most important problems. Nowadays, H1N1 screening at KLIA for flue detection is done manually. Therefore, this project will detect and count the head for H1N1 screening automatically by applying image processing. The head count will be done at KLIA to monitor the total passenger that will undergo H1N1 screening for record. However, the head count of H1N1 screening is complex since crowded people will lead to overlapping head and head detection will be hard to accomplish. A method based on implementation of Hough transform is applied. This project can detect human head effectively in complex background, and provide a new approach of human head detection especially when the colour information of image is limited. Other than that, shape detection for roundness head will be used as an additional method. Besides that, I also use other method which is cropping and mapping method. Thus, by implementation of one of these methods, the head detection can be automatically counted in order to monitor the passenger that undergoes H1N1 screening at KLIA. The expected outcome of this project is a Graphical User Interface (GUI) in MATLAB that takes thermal images of passenger screening at KLIA and output detected the head in the images with total head count. specialized Zalida Wati Ahmad Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2012 Bibliography : p.[45-49] Image intensifiers Electronic cameras THE0007092(Local) UMP 130815 20251114204542.0 vtls000073786