臺灣博碩士論文加值系統

近年來，由於獸醫師執業人數迅速的攀升，加上獸醫師工作瑣碎繁雜，許多動物經診療結束後需要親自持續觀察，但因缺乏一套輔助動物診療資訊系統，而降低獸醫師的工作效率。為了解決獸醫師親自觀察的問題並提高工作效率，因此，本研究基於影像技術針對生病需觀察動物進行監測，設計並建置一套輔助獸醫師診療系統－「以影像技術為基礎之動物診療輔助系統」，包括：(1)動物影像擷取定位模組－藉由CamShift顏色追蹤技術，針對監測動物進行定位，利用光流演算法計算前後Frame移動向量大小，藉此分類大動作與小動作影像，獸醫師進階定義樣本影像，提供後續辨識；(2)動物行為特徵點萃取及辨識模組－根據加速強建特徵(Speeded-up Robust Features, SURF)演算法，將即時影像及樣本影像進行匹配，藉此分析及記錄動物是否出現樣本影像之行為，提供獸醫師查詢歷史紀錄；(3)動物診療紀錄模組－藉由本影像監測、辨識結果及醫療影像資訊建置動物基本資訊平台，輔助獸醫師能快速瞭解動物歷史診療及用藥紀錄，並依據各影像紀錄資訊瞭解該動物在不同時期的成長過程。本系統根據影像監控與辨識技術，藉由自動化偵測與紀錄差異影像及辨識行為監測之功能，主動提醒獸醫師能即時掌握動態警示資訊，藉此快速回應動物所發生的緊急狀態與達到輔助獸醫師診療之目的。

In recent years, the numbers of veterinarians increase rapidly, and it's very complicated job. The veterinarians have to examine those animals continually after their treatment, and it will decrease the veterinarians work efficiency due to the integral animal diagnosis support system were lacked. In order to solve the problem that veterinarians observe personally and improve the efficiency of work. Therefore, this study designed and built an animal diagnosis support system using image technology to improve veterinarian’s work efficiency, and included three modules as below: (1) Animal Image Extraction and Feature Location Module-We used CamShift automatic color tracking technology to orientate the animals, and calculated the vector of frame before and after by Optical Flow algorithm to classify the different motions. However, the veterinarian could define the sample images for the identification in the future; (2) Animal Behavior Feature Extraction and Recognition Module-According to the Speeded-up Robust Features (SURF) algorithm, we compared the prompt images of animals’ behavior with sample images to analyze and record if the animals had same behavior with sample images for veterinarians’ history record; (3) Animal Clinic Records Module-We built animal information platform with image monitoring, identification result and medical image information to assist veterinarians understand animal’s remedy history and medical record. This platform could also help the veterinarians understand the animals’ growth process in different period by every images record. Furthermore, according to the images monitor and identification technology, this system could assist veterinarians to know well the automatic alert information with its auto detect, difference images and behavior identification monitor function. This system could responded animals’ emergent situation and achieves the goal of assist veterinarians’ treatment.

目錄
摘要 I
ABSTRACT II
謝誌 IV
目錄 V
圖目錄索引 VIII
表目錄索引 X
第1章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 4
1.3 研究流程 7
1.4 論文架構 8
第2章 文獻探討 9
2.1 動物影像相關應用 9
2.1.1 動物分類辨識 9
2.1.2 動物影像紀錄與追蹤 10
2.2 影像相關應用介紹 11
2.2.1 行車安全之應用 11
2.2.2 社區與居家安全之應用 12
2.2.3 醫療領域之應用 14
2.3 影像相關技術介紹 15
2.3.1 背景偵測 15
2.3.2 色彩空間 15
2.3.3 二值化 16
2.3.4 邊緣偵測 16
2.3.5 特徵擷取 18
2.3.6 光流法 21
第3章 研究方法 25
3.1 系統架構 25
3.2 動物影像擷取定位模組 28
3.3 動物行為特徵點萃取及辨識模組 41
3.4 動物診療紀錄模組 53
第4章 系統實作 56
4.1 實作環境 56
4.2 系統需求規劃與功能設計 57
4.3 系統展示 58
4.4 實驗對象 72
4.5 動物行為影像辨識實驗 73
4.6 系統使用滿意度調查 74
第5章 結論與未來發展 77
5.1 結論 77
5.2 未來研究方向 78
5.3 研究限制 79
參考文獻 81
作者簡介 89
附錄 90

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