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研究生:黃錡
研究生(外文):Chi Huang
論文名稱:基於邊緣資訊與幀差建立一個強健的移動物件偵測方法
論文名稱(外文):Robust Detection for Moving Objects Based on Edge Information and Frame Differences
指導教授:林道通
指導教授(外文):Daw-Tung Lin
口試委員:林道通莊仁輝陳謀琰
口試委員(外文):Daw-Tung LinJen-Hui ChuangMou-Yen Chen
口試日期:2014-07-24
學位類別:碩士
校院名稱:國立臺北大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:英文
論文頁數:41
中文關鍵詞:邊緣偵測動量偵測動量估計影像監控
外文關鍵詞:edge detectionmotion detectionmotion estimationvideo surveillance
相關次數:
  • 被引用被引用:0
  • 點閱點閱:675
  • 評分評分:
  • 下載下載:38
  • 收藏至我的研究室書目清單書目收藏:0
居家安全和公共監控在日常生活中是必須且不可缺少的。通過監控影像的分析,人
們可以針對特定的空間做控管,也可限制特定空間的進出情形。本篇論文提出使用
虛擬閘門技術的智慧型影像監控系統來做移動物體檢測,在影像監控時,虛擬閘門
可以取代人類的工作。在實際應用時是透過四通道的NVR來傳送連續影像,並且四
通道的影像可以同時運算。虛擬閘門的方法是基於動量估計,會去檢測移動物體的
方向,並檢查他們是否通過虛擬閘門。因此虛擬閘門不需要背景建模並且能夠在極
其複雜的情況下適用。在實際應用時,光線的變化是需要考慮的,例如紅外攝影機
會自動切換到夜間模式,或是在夜間,保全人員用利用手電筒巡邏。因此,根據上
述的問題,本文提出一個新的方法,在照明條件大幅變化下,依舊可以正常的做移
動物體檢測。

Home security and public monitoring are essential to daily life. By using surveillance video analysis, people can control access for particular spaces. This paper presents the object detection using proposed virtual gate technique for intelligent video surveillance. The virtual gate obviates the need for humans in the work of surveillance. This application also can accept sequential images from real-time video obtained using a four-channel network video recorder which transmitted to a computer. The virtual gate method is based on motion estimation; it detects the direction of moving objects and examines whether they will pass through the virtual gate. The virtual gate thus does not require background modeling and can be applied in extremely complex situations. Actual application scenarios require that changes in light be considered. For instance, IR cameras automatically switch to night mode, and during the night, security personnel use flashlights to patrol. Thus, this paper presents an advanced method for moving object detection according to which problems pertaining to substantial changes in lighting conditions can be addressed.
Abstract i
Acknowledgements ii
Contents iii
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Thesis Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Literature Survey 5
3 Motion Detection Algorithm 8
3.1 Mean Squared Error Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.2 Three-Step Search Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . 12
4 Motion Vector Analysis 15
4.1 Mean Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.2 Motion Vector Direction Analysis . . . . . . . . . . . . . . . . . . . . . . . . 17
4.3 Detection of Changes in Lighting Conditions . . . . . . . . . . . . . . . . . . 18
4.4 Illumination Noise Removal . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
5 Virtual Gate Object Detection And Justification Criteria 23
6 Virtual Gate Operation Procedure 26
7 Experimental Results 30
8 Conclusion and Future Work 35

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