結合自聚類的寵物狗身分識別

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姓名

李書宇(SHU-YU LI) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

結合自聚類的寵物狗身分識別
(Pet identity recognition combined with auto-clustering)

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至系統瀏覽論文 (2026-8-3以後開放)

摘要(中)

本論文提出使用兩階段的辨識方法應用在寵物狗的身分識別，針對輸入影像以其外在的生物特徵進行初步的分群，將外在特徵相似的影像劃分到同一群集，並以臉部定位對影像進行校正，以消除拍攝照片時因外在因素所產生之誤差並將影像以狗臉的邊框進行正規化，再以LBP進行特徵轉換獲得紋理的特徵圖，並以孿生網路的架構對正規化後的影像進行影像比對，以歐式距離計算輸入影像與系統資料庫已註冊影像相似度，我們以農委會提供的犬隻資料集進行實驗，可達87%的辨識率。

摘要(英)

In this paper, a two-stage identification method is proposed for pet dog identification. The input images are initially grouped by their external biometric features, and the images with similar external features are classified into the same group, and the images are corrected by face feature localization to eliminate the errors caused by external factors when taking photos.The similarity between the input images and the registered images in the system database was calculated by using the Euclidean distance, and we were able to achieve 87% recognition rate by using the data set of dogs provided by the Council of Agriculture Executive Yuan.

關鍵字(中)

★ 身分識別
★ 狗

關鍵字(英)

論文目次

摘要 I
Abstract 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 1
1.2 研究目標 3
1.3 論文架構 3
第二章、文獻回顧 4
2.1 影像切割 4
2.1.1 YOLO影像切割 4
2.1.2 U-NET語義分割 6
2.2 影像自聚類 8
2.2.1 使用全卷積Auto-encoder的影像自聚類 8
2.2.2 Resnet 殘差神經網路 10
2.3 影像特徵轉換 12
2.3.1 局部二值模式 12
2.4 影像定位 19
2.4.1 MTCNN 19
2.5 影像特徵點辨識 23
2.5.1 Facenet 24
第三章、寵物狗身分識別系統設計 29
3.1 寵物狗身分識別系統架構設計 30
3.2 寵物狗身分識別系統離散事件建模 36
3.2.1 影像自聚類Grafcet 39
3.2.2 臉部偵測/定位Grafcet 41
3.2.3 特徵轉換Grafcet 42
3.2.4 影像辨識Grafcet 43
3.2.5 註冊/比對Grafcet 43
第四章、系統整合與實驗 45
4.1 實驗環境與資料庫 45
4.2 寵物狗偵測 48
4.3 自聚類實驗 52
4.4 影像定位實驗 56
4.5 影像特徵轉換實驗 61
4.6 影像辨識實驗 62
4.7 孿生網路比較實驗 66
4.8 討論 68
4.9 未來展望 69
參考文獻 70

參考文獻

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指導教授

陳慶瀚

審核日期

2021-8-4

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