臺灣博碩士論文加值系統

此篇論文中，利用攝影機配合影像處理設計一居家照護偵測並自動通報老年人是否跌倒的方法，達到提高日常生活中獨自在家的老年人之安全性。本文研究主要應用攝影機取得的影像，經由得到的即時影像與原先建立好的背景影像相減，進而利用色彩轉換、形態學處理等影像處理方法，結合影像追蹤及感興趣區域技術來得到影像中監測人物的姿態，並進一步判斷人體是否為倒下，當系統判定出人體出現為跌倒狀態的同時透過Skype傳送即時訊息警告。實驗結果證實本論文所提出的影像偵測及自動通報系統能夠確實的偵測出人體跌倒事件以及即時傳送警告訊息，以達到偵測居家老人是否跌倒及能即刻就醫的安全性。

In this thesis, we proposed an image processing methods to design a home care detection and alarm system which can justify whether the elder falls down or not. It is used to improve the safety when they stay at home alone. In this study, the images are obtained by video camera. After the original background image is obtained, the image will subtract the pre-established image. And then, we use image processing methods such as color format transform, morphological processing combined tracking technology and region of interest technology to detection human attitude in the image. When the human is falling down, the system will transmit message by Skype immediately. The experimental results show that the proposed image processing technology and automatic alarm system can achieve the purpose of both detection seniors’ situation and transmit message immediately. The safety of elder can be protected and seek medical care straightaway.

目錄
中文摘要.....................................i
英文摘要.....................................ii
誌謝........................................iii
目錄........................................iv
圖目錄.......................................vii
表目錄.......................................x

第一章 緒論...................................1
1.1 研究背景與動機 .............................1
1.2 研究方法..................................3
1.3 論文結構..................................5
第二章 影像處理理論與人體辨識 .....................7
2.1 系統架構..................................7
2.2 色彩空間..................................8
2.2.1 RGB色彩空間............................9
2.2.2 HSI色彩空間 .............................11
2.3 偵測區域..................................15
2.4 特定區域處理...............................16
2.5 背景相減..................................17
2.6 影像二值化.................................19
2.7 影像形態學處理 .............................20
2.8 特徵點擷取.................................24
第三章 跌倒通報系統 .............................28
3.1 前言 .....................................28
3.2 WiMAX....................................32
3.3 無線個人網路...............................32
3.3.1 藍芽....................................33
3.3.2 超寬頻..................................34
3.3.3 近距離無線通訊............................35
3.3.4 WiFi...................................35
3.4 3G.......................................36
3.5 Skype發展與技術............................36
3.5.1 Skype網路架構............................37
3.5.2 Skype通訊埠 .............................38
3.5.3 Skype加密機制............................40
3.5.4 Skype API功能...........................40
3.5.5 Skype API分類...........................42
3.5.6 Windows上Skype API連結控制...............44
3.5.7 Skype Develop Tool.....................46
3.6 小結......................................51
第四章 實驗結果.................................52
4.1 前言......................................52
4.2 影像模擬結果...............................53
4.3 模擬結果...................................62
第五章 結論與未來展望............................79
5.1 結論......................................79
5.2 未來展望...................................80
參考文獻.......................................81

圖目錄
圖1. 1 人體目標標示圖............................4
圖2. 1 系統動作流程圖............................7
圖2. 2 RGB色彩立方圖............................10
圖2. 3 RGB與HSI色彩空間模型關係圖.................11
圖2. 4 HSI色彩空間示意圖.........................12
圖2. 5 影像處理程序圖............................15
圖2. 6 特定偵測區域.............................16
圖2. 7 二值化影像處理圖..........................19
圖2. 8 形態學影像處理............................20
圖2. 9 侵蝕運算示意圖............................21
圖2. 10 膨脹運算示意圖...........................22
圖2. 11 斷開運算示意圖...........................23
圖2. 12 閉合運算示意圖...........................24
圖3. 1 無線網路種類(範圍大至小)...................31
圖3. 2 無線個人區域網路技術比較圖...................33
圖3. 3 Skype網路架構圖..........................37
圖3. 4 Skype設定需要使用的Port...................39
圖3. 5 Skype API訊息回應架構.....................41
圖3. 6 Labview與Skype連結流程圖..................44
圖3. 7 Skype API存取控制列表.....................45
圖3. 8 Skype管理API之存取控制.....................46
圖3. 9 Skype API Tracer........................47
圖3. 10 Skype API Tracer溝通指令.................47
圖3. 11 輸入PING指令時顯示之畫面...................48
圖3. 12 輸入GET SKYPEVERSION指令時顯示畫面.........48
圖3. 13 輸入GET USERSTATUS指令時顯示畫面...........49
圖3. 14 輸入SEARCH FRIENDS指令時顯示畫面...........49
圖3. 15 輸入SEARCH USERS <target>指令時顯示畫面....50
圖4. 1 人體姿態判斷程序圖..........................53
圖4. 2 場景A人體姿態站立圖.........................54
圖4. 3 場景A人體姿態蹲下圖.........................54
圖4. 4 場景A人體姿態跌倒圖.........................55
圖4. 5 場景B人體姿態站立圖.........................55
圖4. 6 場景B人體姿態蹲下圖.........................56
圖4. 7 場景B人體姿態跌倒圖.........................56
圖4. 8 場景C人體姿態站立圖.........................57
圖4. 9 場景C人體姿態蹲下圖.........................57
圖4. 10 場景C人體姿態跌倒圖........................58
圖4. 11 場景D人體姿態站立圖........................58
圖4. 12 場景D人體姿態蹲下圖........................59
圖4. 13 場景D人體姿態跌倒圖........................59
圖4. 14 場景E人體姿態站立圖........................60
圖4. 15 場景E人體姿態蹲下圖........................60
圖4. 16 場景E人體姿態跌倒圖........................61
圖4. 17 系統模擬結果圖(站立).......................62
圖4. 18 系統模擬結果圖(蹲下).......................62
圖4. 19 系統模擬結果圖(跌倒).......................63
圖4. 20 系統模擬結果圖(跌倒時傳送即時訊息)............63
圖4. 21 手機接收端Skype畫面.......................64

表目錄
表2. 1 軸區域範圍 ...............................17
表4. 2 實驗辨識測試表.............................65
表4. 3 實驗統計表................................78

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