無線視覺感測網路(Wireless Visual Sensor Networks，WVSNs)是由許多分散在場景中的視覺感測節點所構成。相較於傳統的無線感測網路(Wireless Sensor Networks，WSNs)而言，無線視覺感測網路不僅能達到監控之功用，並且能夠進一步取得影像資訊，如此一來將更能有效地立即掌控監控場景之現況。這也使得無線視覺感測網路中之防禦線覆蓋(barrier coverage)問題受到許多研究學者的重視。然而，此問題有著許多的挑戰，原因在於WVSNs所收集的資料為影像資訊，若使用過多的視覺感測節點佈建防線，將收集到過多且不必要之影像。如此一來，將增加影像回傳時所需的頻寬負載。並且，過多重覆影像也將造成後端影像處理之困難度。因此，如何挑選較少數量的視覺感測節點來佈建防線，已成為無線視覺感測網路中一項非常重要之議題。此外，過往針對無線視覺感測網路下之防禦線覆蓋研究，並未考慮到其所收集到的每一片段影像應具有一定大小之影像厚度，如此一來將難以辨視其所收集到的影像。因此，本研究將加入影像厚度之考量，藉此提供較佳之監控品質(Quality of Monitor, QoM)。
此外，當有入侵者穿越防禦線時，過往的視覺防禦線只能確保該入侵者在穿越防禦線時其影像資訊能夠被偵測並擷取下來，但並無法保證其所擷取到的影像資訊為入侵者之重要部分。因此，為了更進一步的提升QoM，我們將加入影像重要性(Importance of Image, IoI)之考量，藉由加入環繞覆蓋(encircled coverage)，來提供入侵者之環繞影像資訊，如此一來，將可確保重要角度之影像能夠被擷取下來。綜合上述各點，本研究將針對無線視覺感測網路中之防禦線覆蓋問題重新做一探討，並提出分散式的視覺防禦線建構演算法，藉以找尋較少數量之視覺感測節點來佈建具備一定影像監控厚度及環繞覆蓋能力之防禦線。

Wireless visual sensor networks (WVSNs) can not only provide monitoring functions like wireless sensor networks (WSNs) but also capture real-time images of the monitored scene. This capability has made the barrier coverage of WVSNs an issue of interest to many researchers. For instance, in the construction of a barrier,   using too many camera sensors may produce an excessive number of redundant and overlapping images, which in turn increase the bandwidth of data transmission,   occurrence of packet collisions, and difficulty of post image processing.   Therefore, how to use a minimum number of camera sensors to construct a barrier has become an important issue in WVSNs. Besides, previous research of barrier coverage did not consider breadth of coverage, i.e. the width of collected images.   In this paper, we consider breadth and Importance of Image (IoI) to increase the Quality of Monitor (QoM) of WVSNs. Finally, the proposed algorithms’ successful rate of barrier construction under different conditions, including β requirement,   sensor distribution, and rotation capability is also tested through simulations.

圖目錄	VI
表目錄	IX
第一章、簡介	1
第二章、相關研究	8
2.1WSNs中Barrier Coverage Problem之相關研究	8
2.2WVSNs中Barrier Coverage Problem之相關研究	10
第三章、問題之正規化及系統模型	13
第四章、防禦線建構演算法	17
4.1建構具β-QoM等級品質保證之防禦線	17
4.2建構具β-IoI等級品質保證之防禦線	30
第五章、實驗分析及模擬	43
5.1D-TriB以及D-TriBR的實驗模擬	43
5.2D-eTriB以及D-eTriBR的實驗模擬	49
第六章、結論	56
參考文獻	58
附錄-英文論文	63

圖目錄
圖 1. Crossing Paths以及Non-Crossing Paths	2
圖 2. Weak Barrier以及Strong Barrier	3
圖 3. 不具厚度考量以及具厚度考量之影像監控	3
圖 4. 影像資訊重要性之比較	4
圖 5. 厚度示意圖	5
圖 6. 環繞覆蓋之示意圖	5
圖 7. 幅角限制之示意圖	13
圖 8. 扇形區域示意圖	13
圖 9. Virtual Line Function	18
圖 10. Virtual Line 轉換示意圖	19
圖 11. 防禦線挑選示意圖	21
圖 12. 直線L與視覺感測節點vi之FoV交於兩點	22
圖 13. 最小厚度計算示意圖	23
圖 14. Basic Distributed β-Breadth Belt-Barrier Construction Algorithm without rotation (D-TriB)	26
圖 15. 轉動後所能提供之貢獻度示意圖	27
圖 16. 順逆時鐘轉時所需轉動角度之示意圖	28
圖 17. 轉動角度對應關係之示意圖	29
圖 18. Rotation Function	29
圖 19. 防禦線挑選示意圖	33
圖 20. 節點貢獻度之示意圖	34
圖 21. 兩視覺感測節點之合作示意圖	35
圖 22. 三個視覺感測節點合作示意圖	37
圖 23. 四個視覺感測節點合作示意圖	38
圖 24. Basic Distributed β-Breadth Belt-Barrier Encircled Coverage Construction Algorithm without rotation (D-eTriB)	40
圖 25. 三個節點藉由轉動所能建立之最大環繞覆蓋區域	42
圖 26. 新加入節點藉由轉動所能夠建立之環繞覆蓋區域	42
圖 27. 隨機分佈	44
圖 28. 在不同λ值下之卜瓦松分佈	44
圖 29. 不同撒落間隔下之節點密度分佈(節點總數為100個)	45
圖 30. 在不同空投點的間隔下之高斯分佈	46
圖 31. 在不同β值下之隨機分佈(節點總數為200個)	47
圖 32. 在不同β值下之卜瓦松分佈(λ=8，節點總數為200個)	48
圖 33. 在不同β值下之高斯分佈(空投點的間隔為20，節點總數為200個)	48
圖 34. 在不同β值下之高斯分佈(空投點的間隔為20，節點總數為100個)	48
圖 35. 隨機分佈	50
圖 36. 在不同λ值下之卜瓦松分佈	50
圖 37. 不同撒落間隔下之節點密度分佈(節點總數為1600個)	52
圖 38. 在不同空投點的間隔下之高斯分佈	52
圖 39. 在不同β值下之隨機分佈(節點總數為2800個)	54
圖 40. 在不同β值下之卜瓦松分佈(λ=7，節點總數為2800個)	54
圖 41. 在不同β值下之高斯分佈(空投點的間隔為20，節點總數為2800個)	54
圖 42. 在不同β值下之高斯分佈(空投點的間隔為20，節點總數為1400個)	55

表目錄
表 1. 模擬參數_1	43
表 2. 模擬參數_2	49

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