適用於低頻寬無線傳輸之智慧型監控系統; For low-bandwidth wireless transmission intelligent monitoring system

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Electrical Engineering > Electronic Thesis & Dissertation > Item 987654321/61841

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/61841

Title:	適用於低頻寬無線傳輸之智慧型監控系統;For low-bandwidth wireless transmission intelligent monitoring system
Authors:	黃至祺;Huang,Chih-Chi
Contributors:	電機工程學系
Keywords:	影像辨識;無線傳輸
Date:	2013-11-08
Issue Date:	2014-02-13 17:52:21 (UTC+8)
Publisher:	國立中央大學
Abstract:	智慧家庭生活是一種趨勢，不僅是年輕一代，在中年老年人間也愈來愈受歡迎。智慧家庭當中，無線網路、感測器和中央伺服器扮演著重要的腳色，感測器利用無線網路傳送重要的資訊給中央伺服器判斷，來達成電器控制，控制環境，安全監控的功能。雖然有許多不同的感測器，但是卻很少出現攝影機，原因是影像的資訊量過於龐大，在無線傳輸的傳輸率下是種挑戰，為了達成這個目標，我們將攝影機擷取到的資訊先分離出前景，然後使用tracking的演算法抓住物件，接著在使用一個專門壓縮前景的演算法做高倍率的binary壓縮，再透過無線傳輸，這樣我們的中央伺服器即可還原物件的輪廓，再透過地圖資訊的資料，我們可以定位出家庭裡的物件資訊。在此篇論文中我們將使用攝影機加上linux的嵌入式平台，來模擬感測器搭，再配無線通訊模組，並且使用PC來當作中央伺服器，來實現智慧家庭的功能，我們使用320240的影像大小，成功的達成一秒8張以上的處理速度。 Smart Home is a trend, not only the younger generation, in the elderly is also increasing in popularity among. In the smart home, wireless networks, sensors and the central server plays an important role, sensors send over the wireless network is important information to the central server judgment, to achieve electrical control, control environment, security and surveillance. Although there are many different sensors, but few cameras because the image is too large amount of data, the transmission in the wireless transmission rate is a challenge, in order to achieve this goal, we will segmentation the foreground image, and then using a special algorithm do high performance binary compression, then through the wireless transmission, the central server can restore contour of the object, and then use map information data, we can locate objects in the family. In this paper we will use the video camera and embedded linux platform to simulate sensors with wireless communication module, and to use the PC as a central server, to achieve the smart home features, we use 320 240 image size, the success of reaching more than 8fps.
Appears in Collections:	[Graduate Institute of Electrical Engineering] Electronic Thesis & Dissertation

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