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研究生:歐陽寧
研究生(外文):Ning, Ouyang
論文名稱:影像特徵點匹配應用於景點影像檢索
論文名稱(外文):Image Feature Point Matching on Landmark Image Retrieval Applications
指導教授:鄭旭詠
指導教授(外文):Hsu-Yung Cheng
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文出版年:2013
畢業學年度:101
語文別:中文
論文頁數:77
中文關鍵詞:影像特徵景點影像檢索
外文關鍵詞:image featurelandmark image retrieval
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隨著科技的發展,隨身攜帶的設備像是智慧型手機與平板非常普遍,這些設備通常都具備著全球地位系統(GPS)能夠定位出現在大概的位置,這對旅客是非常有用的資訊,然而,當人們在旅行時,光憑GPS的位置資訊並不能給予正確且明確的景點資訊,有時當旅客站在遠方觀察景點時,同時會觀察到許多景點在同一位置上,處在這種情形之下,當旅客希望取得某個景點資訊,必須查詢所有附近的景點試著取得想要的資訊,隨著智慧性設備都具備著相機的功能,我們提出一個應用程式利用拍照取得影像結合GPS取得地點位置資訊快速地回應使用者想要的景點資訊。使用者可以輕易地照相與點擊按鈕查詢相關知名的旅遊網站。
本系統利用Google Place API取得周邊地點的名字與類型,首先過濾這些地點取得候選的景點,接著使用候選景點的名字,當作關鍵字去大眾搜尋引擎取得景點影像,對回傳的影像會使用局部特徵匹配技術作確認。本論文使用Speeded Up Robust Feature (SURF)特徵與Oriented FAST and Rotated BRIEF (ORB)特徵,本系統藉由影像特徵匹配技術去確認出正確的景點影像,我們也使用FLANN函式庫建立隨機k維樹(Randomized k-d tree),確認景點名字後,本系統可以使用正確的景點名字查詢知名旅遊網站,並將搜尋結果呈現給使用者。我們做了許多實驗去比較不同特徵還有不同參數的設定,並展示本系統的可靠與有效性。

With the development of technology, portable devices such as smart phones and tablets have become prevalent. These devices are often equipped with Global Positioning System (GPS) and are able to locate its current approximate location. Such information is very useful for travelers. However, when people are travelling, the GPS readings alone could not accurately give the exact landmark information to the device carriers. Sometimes the travelers would observe a landmark from a distance. In addition, multiple landmarks could be observed at the same place. Under such circumstances, if the travelers wish to retrieve the landmark information, they would need to look up all the landmarks nearby and try to get the information they are looking for. Since the portable devices are also equipped with cameras, we propose an application that can utilize the images captured by the cameras and the location information acquired by the GPS readings and rapidly return the desired landmark information to the users. The user can easily take a photo and touch a button to search for the correct landmark information from famous travel websites.
The proposed system takes advantage of the Google place API and gets the names and types of the nearby places of the current GPS reading. The names are filtered first to get the landmark candidates. Then the keywords of these landmark candidates are used to query the image database of the public search engines. The returned images are then confirmed by the system using local feature matching techniques. In the thesis, we use Speeded Up Robust Feature (SURF) and Oriented FAST and Rotated BRIEF (ORB) features. The system analyzes these images by feature matching to confirm the correct image of the landmark. We also use FLANN library to construct randomized k-d tree. After confirming the landmark name, the system would query the famous travel websites using the correct landmark name and return the search results to the users. We have performed experiments to compare the performance of different features and parameter settings. We have also demonstrated the feasibility and effectiveness of the proposed application system.

摘要 I
Abstract II
目錄 III
圖目錄 V
表目錄 VII
第一章 緒論 1
1.1 研究動機 1
1.2 文獻回顧 2
1.3 系統使用情境與流程 5
1.4 論文架構 8
第二章 特徵方法回顧 9
2.1 SURF(Speed up Robust Feature) 9
2.1.1 積分影像法(Integral Image) 9
2.1.2 SURF 基於 Hessian-Matrix 的特徵點偵測 10
2.1.3 SURF尺度空間表示 12
2.1.4 SURF定位有興趣之特徵點 13
2.1.5 SURF方向指派 14
2.1.6 SURF特徵描述子 15
2.2 ORB特徵回顧 ( oFAST + rBRIEF) 16
2.2.1 FAST 特徵偵測 16
2.2.2 由中心強度(centroid intensity)決定方向 18
2.2.3 增加旋轉向量的BRIEF描述子( Steered BRIEF) 18
2.2.4 學習好的2位元特徵 20
第三章 系統說明與影像相似度 21
3.1 系統說明 21
3.1.1 取得經緯度資訊 21
3.1.2 取得地點資訊與過濾 22
3.1.3 取得地點圖片 25
3.2 系統介面功能說明 26
3.3 影像特徵匹配與驗證方法 28
3.3.1 匹配與驗證方法 30
3.3.2 極線幾何基本矩陣說明 32
3.3.3 隨機抽樣一致演算法(RANSAC)驗證 35
3.4 FLANN建立k-d tree與驗證方法 37
3.5 影像比對流程 40
第四章 實驗結果與分析 42
4.1 系統環境與測試資料 42
4.2 實驗結果與分析 43
第五章 結論與未來研究方向 52
參考文獻 53
附錄A JNI (Java Native Interface) 59
JNI 使用說明 59
中文字串處理 61
使用OpenCV注意事項 61
附錄B 可交換圖像文件(EXIF) 62
附錄C J SON(JavaScript Object Notation) 64
取得資料方法 64
JSON 資料格式分析 65

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