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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

街道特徵與地標位置識別之研究 / Content-based map localization using street map with landmarks

李澤毅, Li, Ze Yi Unknown Date (has links)
隨著GIS的發展,地圖定位成為空間查詢中極為普遍的行為。一般地圖定位大多透過地址來進行,但是在缺乏地址的情況之下,進行地圖上之定位變成極為困難之事。 本論文嘗試對手繪地圖在真實地圖上進行定位,我們提出了一套機制,使用者可以隨意地以手繪方式繪製街道圖與地標,透過我們提出的方法,即可自動地在真實的地圖上進行定位。 論文中,我們使用相鄰街廓中之地標配置與相鄰之交叉路口之地標配置等變數組成的表示法來描述地圖。我們將手繪地圖與真實地圖轉換成這些表示法,並透過字串編輯距離、圖同構等關係來比較手繪地圖與真實地圖之相似度,從而對手繪地圖進行定位。 實作中,我們挑選了幾處真實場景在台北市地圖中進行比對並觀察其結果。系統採用之地標包括政府機構(如派出所、消防隊、區公所等)、學校、醫院等資料。在實驗中,應用這套表示法可成功的定位出使用者所輸入之各場景所在位置。另外,透過控制相似度門檻值,我們可以調整辨識之精確度,不至於錯失可能之定位結果。 / As the widely spread of the GIS applications, map localization becomes one of the most important features in the spatial information retrieval. Normally, map localization is done through street addresses. Without this information, map localization becomes very difficult. In this research, we are trying to do map localization using hand drawing maps. We proposed a mechanism that can localize the user's drawing map in the reference map automatically. Our approaches use the landmark configurations of the adjacent street blocks as well as the landmark configurations of the adjacent street intersections as the descriptors in representing a map. The user's hand drawn maps and the reference maps are converted into these representations. The string editing distances and graph isomorphism are used in determining the similarities between the hand drawn map and the reference map. The map localization can be done by comparing these similarities. We used various real scenes in Taipei City to verify our systems. The landmarks we used including police offices, fire stations, county offices, schools and hospitals, etc. The experimental results shown that our system can localize the user's input successfully. Moreover, by controlling thresholds in similarity analysis, we can adjust the system's accuracy that reduces possibility of miss localizations.

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