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    Please use this identifier to cite or link to this item: http://ccur.lib.ccu.edu.tw/handle/A095B0000Q/564

    Title: 基於Bit-plane分解與重組應用於移動物體偵測;Bit-plane decomposition and restructuring for moving object detection
    Authors: 簡至燿;JIAN, ZHI-YAO
    Contributors: 資訊工程研究所
    Keywords: Bit-planes;hyper bit-plane;遲滯閾值;視頻監視;運動補償;Bit-planes;hyper bit-plane;hysteresis threshold;video surveillance;motion compensation
    Date: 2017
    Issue Date: 2019-07-17
    Publisher: 資訊工程研究所
    Abstract: 近年來,視頻監控越來越受歡迎,視頻監控技術的發展已不可或缺,因為它可以降低人工成本和檢測錯誤率。大多數視頻監控攝像機是固定的,因此對背景建模的發展需求增加。當運動對像出現在視頻中時,運動對像被稱為前景對象,其可以通過“背景減除”來提取,在視頻監控中,移動物體檢測已經成為自動了解視頻內容的核心技術之一。儘管已經提出了許多檢測方法,但是它們仍然具有一些問題,諸如運動對象的陰影和不完整形狀。在本論文中,我們對於視頻監控系統中的運動物體對象偵測,利用Bit-planes方法,進行了色彩資訊及YUV色彩空間資訊方面生成hyper bit-plane,而hyper bit-plane利用了YUV色彩空間的資訊抑制了陰影生長,而我們所的方法利用hyper bit-plane作為指標影像,而為了能夠清楚描繪出移動物體的輪廓及完整的移動物體,利用灰階Bit-plane影像作為較低基準的影像資訊,再將hyper bit-plane和低基準的影像資訊結果,利用時間域、空間域的特性,應用於圖像遲滯閾值和運動補償來補償空間和時間信息的損失,經由遲滯閾值和運動補償能夠將移動物體的輪廓及物體作整合。最後、我們將所提出的技術能夠在運用在即時監視系統上所需的效率,以提升視訊監視系統能夠快速做出系統所需要的應用。
    In recent years, video surveillance has become increasingly popular, the development of video surveillance technology is indispensable, because it can reduce labor costs and detection error rate. Most video surveillance cameras are fixed, so there is an increased demand for background modeling. When the motion object appears in the video, the moving object is called the foreground object, which can be extracted by "background subtraction". In the video monitoring, moving object detection has become one of the core technologies of automatic understanding of video content. Although a number of detection methods have been proposed, they still have some problems, such as shadows and incomplete shapes of moving objects. In this thesis, we use the Bit-planes method for the motion object detection in the video surveillance system to generate the hyper bit-plane by the color information and YUV color space information. Hyper bit-plane uses the YUV color space information to suppress the shadow growth, and our method uses hyper bit-plane as the indicator image. In order to describe clearly the complete contours of moving objects, the use of grayscale Bit-plane image as a lower benchmark image information, and use spatial and temporal information to integrate hyper bit-plane and low Image information results, that applied to the image hysteresis threshold and motion compensation to compensate for the loss of space and time information, that can obtain complete foreground through the hysteresis threshold and motion compensation. Finally, we will be able to use the method in the real-time surveillance system.
    Appears in Collections:[資訊工程學系] 學位論文

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