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ITS » Master Theses » Teknik Elektro - Telematika S2
Posted by aprill@is.its.ac.id at 18/11/2015 15:10:43  •  1116 Views


DETEKSI ASAP PADA VIDEO KEBAKARAN DENGAN MOTION TEXTURE FEATURES MENGGUNAKAN SUPPORT VECTOR MACHINE

VIDEO BASED SMOKE DETECTION BASED ON MOTION TEXTURE FEATURES USING SUPPORT VECTOR MACHINE

Author :
SUSANTO, HERU EKO ( 2212206705 )




ABSTRAK

Saat ini banyak gedung yang hanya digunakan pada waktu-waktu tertentu saja. Pada saat tidak digunakan gedung-gedung tersebut hanya dijaga oleh beberapa orang secara bergantian atau bahkan tidak dijaga. Untuk membantu mengawasi gedung dari tindak kejahatan seperti pencurian dan perampokan dipasang sistem pengamatan berbasis video surveillance pada ruangan-ruangan gedung tersebut. Sedangkan untuk mencegah dari bahaya kebakaran pada ruangan gedung juga dipasang sensor asap. Keberadaan asap selain dapat dikenali keberadaannya menggunakan sensor asap juga terlihat melalui kamera pengawas. Dengan demikian video citra keluaran kamera pengawas dapat digunakan untuk mendeteksi keberadaan asap dalam ruangan. Dalam penelitian ini akan diterapkan sebuah metode deteksi asap didalam ruangan berbasis citra digital menggunakan motion texture features. Asap pada video kejadian kebakaran dipisahkan dari objek latar belakang dengan menggunakan pemodelan latar belakang menggunakan Mixture of Gaussian Background Segmentation. Analisis gerakan tekstur kontur dilakukan untuk mendapatkan tur vektor untuk mesin klasi kasi. Klasi kasi dengan Support Vector Machine SVM digunakan untuk menentukan keberadaan asap. Sistem yang dibangun dapat mendeteksi keberadaan asap dengan akurasi deteksi diatas 91.3 error terendah 5 dan yang terburuk 17.


ABSTRACT

Today many building are only used at certain times only. When not in user the buildings are guarded only by few persons alternatelyy or even unmain- tained. To help oversee the building from a crime such as theft and robbery a video surveillance system installed at there. Meanwhile to prevent from re hazard the building is equipped with indoor smoke sensor. If there is a are smoke can be seen clearly on the presence of video surveillace camera. Thus the image from video surveillance cameras can be used to detect the presence of smoke in room. In this study a method will be applied to detects smoke in the room using a digital image based on motion and texture features. The smoke separated from its background objects by a Mixture of Gaussian background segmentation. Contour velocitys contour textures analysis is performed to obtain feature vectors for the classi cation Support Vector Machine SVM for determining the presence of smoke. Fairly good result obtained with system could recognize smoke presence 91 with min error rate 5 and the worst error recognition 17.



KeywordsSmoke Detection; Video Detection; Mixture of Gaussian; Motion Detection; Texture Analysis; Support Vector Machine
 
Subject:  detektor optik
Contributor
  1. Dr. Ir. Yoyon K Suprapto, M.Sc.
  2. Dr. Surya Sumpeno, ST., M.Sc.
Date Create: 18/11/2015
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Master-22103150001549
Collection ID: 22103150001549
Call Number: RTE 621.381 542 Sus d


Source
Master Theses of Electrical Engineering, RTE 621.381 542 Sus d, 2015

Coverage
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Rights
Copyright @2015 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




[ Download - Open Access ]

  1.  ITS-Master-39619-2212206705-Abstract_id.pdf - 287 KB
  2.  ITS-Master-39619-2212206705-Abstract_en.pdf - 885 KB
  3.  ITS-Master-39619-2212206705-Conclusion.pdf - 269 KB




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