本研究提出一個使用手機鏡頭拍攝的書籍封面影像做為辨識對象，透過比對不同於資料庫內的一定範圍角度之書籍封面影像，建構一個根據書籍封面來進行書籍辨識的方法，取代現行使用OCR來辨識書籍的方法。本研究提出的方法是採用SURF特徵點偵測建立資料庫中書籍封面的特徵點資訊後，使用KNN做特徵點的匹配，再透過本研究利用書本特性提出一個根據RANSAC所改良的特徵點篩選方法來改善RANSAC在篩選特徵點匹配的盲點。最後配合本研究基於RANSAC的改良法，提出一個根據Miksik的重複率的判別方法來做為準確率的依據。
本研究將實驗分成兩部分，實驗的第一部份，是影像縮小對於實驗的速度成效驗證和基於RANSAC改良法所制定的閾值範圍實驗；實驗的第二部分，則是測試本研究提出之方法在實際場景的準確度，在使用者將書本拿起進行拍攝的情況下，驗證本研究提出之方法和實驗第一部分中閾值對於本研究方法的準確率影響程度。

This paper provide a way for book recognition by book cover image matching instead of OCR. First, we apply matching process base on SURF, then using nearest neighbor and RANSAC to select the matched candidates. In order to improve the result of matched candidates, we develop a selected method which improves RANSAC's blind spot in matching the feature candidates.
The experiment has two parts; the first part try to find out the effect of input image resizing and the threshold for our own method. The second part is testing the accuracy in experimental environment and reality. We find out that our method's accuracy were achieved about 93% and the accuracy could endured the image rotation up to 15 degrees.

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