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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/8769


    Title: 高空飛行物體之偵測與追蹤;High Altitude Flying Objects Detection and Tracking
    Authors: 吳乃燊;Nelson Wu
    Contributors: 資訊工程研究所
    Keywords: 智慧型監控系統;空防系統;卡曼濾波器;影像處理;image processing;detection;tracking;watershed;kalman filter
    Date: 2003-06-19
    Issue Date: 2009-09-22 11:34:29 (UTC+8)
    Publisher: 國立中央大學圖書館
    Abstract: 近年來,智慧型監控系統一直是熱門的研究項目,而這些研究成果,也多被應用於特殊場所的安全監控系統或特殊路段的交通控管系統當中。在這些相關的研究中,往往依照監控環境與應用目的的不同,系統各環節使用了不盡相同的處理方法,而最終的考量,大抵都是為了達到目標物的偵測與追蹤兩個目的。 在大部分智慧型監控系統的應用與研究,多是針對地面上的行人與車輛,在本篇論文中,我們將這類監控系統的應用推展至空中,希望能夠加強空防系統的效能,因此我們研究了一套針對高空飛行移動物體的偵測追蹤系統。 在偵測與追蹤的過程方面,首先我們利用連續影像間強度的差異來偵測是否畫面中存在飛行移動物體,並配合一些處理,以濾除室外環境中由於光線或其他偶發事件所造成的雜訊干擾,然後再利用影像分割常用的分水嶺分割法,對目標物存在的部分影像區域進行影像分割,以取得目標物的影像資料,如此完成整個偵測流程的處理。之後的追蹤階段,我們利用卡曼濾波器,預測下一個時間點的目標物大略位置座標,再繼續利用分水嶺分割法對預測的位置區域進行影像分割以取得精確的目標物資訊,如此遞迴運作,以達到持續追蹤的目的。 我們以實際拍攝的高空飛行物影像片段來進行系統的實驗,實驗結果也展示出我們的系統在偵測與追蹤高空飛行物方面有相當的正確率與可行性。 Recently, abundant researches relating to unsupervised surveillance systems have been presented which can be applied to security systems and traffic control systems. The composing elements and procedures of these systems are different due to the differences in monitoring environments and application purposes. However, the ultimate consideration is the successful detection and tracking of targets. In most intelligent surveillance systems, the targets that they handle are mainly pedestrians walking and vehicles driving in the ground. In this thesis, we plan to extend the system further to the sky to strengthen the air defense systems by developing a high altitude flying object detection and tracking system. In the proposed system, we firstly detect whether flying objects appear in the surveillance field according to the intensity difference of the pixels in contiguous frames. In this step, some processes need to be performed to remove noises caused by lighting variations or other accidental events. Then, watershed transformation is adopted to segment target images. Next, useful information of targets are extracted from the segmented areas where the targets locate. In the tracking phase, Kalman filter is first employed to predict the possible locations of targets. Then, watershed transformation is applied to the predicting positions to segment the regions. Precise target information can be extracted from the segmented images. Perform the steps repeatedly, we can accomplish the goal of continuous tracking. Experiments were conducted on several image sequences with small targets (aircrafts). Experimental results reveal the feasibility and validity of our proposed system in detecting and tracking high-altitude aircrafts.
    Appears in Collections:[資訊工程研究所] 博碩士論文

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