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Please use this identifier to cite or link to this item: https://repository.uksw.edu/handle/123456789/19552
Title: Pendeteksi Manusia Menggunakan Histogram of Oriented Gradient (HOG) Berbasis Jetson TK1 dan Streaming Via Real-Time Streaming Protocol (RTSP)
Authors: Putri, Tectona Dewa
Issue Date: 2019
Publisher: Program Studi Sistem Komputer FTEK-UKSW
Abstract: The detection process in image processing is an interesting topic and has been developed by many researchers, both those applied to robotics systems and in the security field. In the field of security the use of the camera is realized as a visual sensor for detecting objects and calculating the number of queues. At this time the camera that is often used is Closed Circuit Television (CCTV) cameras, CCTV cameras are able to identify all objects captured by the camera, at the same time the results of CCTV camera detection can be monitored directly through other computer devices. This thesis contains the design of a human object detection system and can stream videos. One method used to detect the presence of human objects is feature extraction using the Histogram of Oriented Gradient (HOG) method that takes the edge or gradient structure that is characterized by local or edge direction with a good local gradient intensity distribution and uses the Support Vector Machine (SVM) classification as separating two classes in two input spaces and for streaming services will use VLC software with the Real-Time Streaming Protocol (RTSP) protocol that functions as communication between the server and the client. Implementation of the system produces the best parameter is γ = 0.000001 and C = 1000 in the training process and the accuracy of the testing reached 97.59%, as well as running a human object detection system that streams with the help of VLC app uses the RTSP protocol with ± 3 second delay.
Description: Tidak diijinkan karya tersebut diunggah ke dalam aplikasi Repositori Perpustakaan Universitas.
URI: https://repository.uksw.edu/handle/123456789/19552
ISSN: 622013005
Appears in Collections:T1 - Computer Systems

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