基於特殊點向量關係的圖像形狀相似性檢測

Shape Similar Image Detection Based on Vector Relationship of Interested Points

林毓超(Yu-Chao Lin)

指導教授 ： 陳志誠

大同大學/經營設計學院/資訊經營學系所/碩士(2010年)

摘要

本論文期望能夠提出一個有效影像檢索之方法，即使影像內容經過旋轉、鏡像依然能夠識別出來。本論文提出的方法，是以CBIR為基礎且只依據影像中物體的外型，避免以關鍵字為依據的檢索系統的準確度不安定，以及關鍵字與影像的管理問題。本論文以針對平面視覺創作物之數位圖像檔案，利用CSS(Curvature-Scale Space)進行特殊點偵測，利用特殊點的相對向量關係作為相似圖像檢索的識別依據以找出可能抄襲的數位圖像檔案。首先從原始圖像中抽出邊緣，接著沿著邊緣點計算其曲率變化以判斷是否為端點。將這些點的向量關係視為連結，並且透過特徵向量投影並將特殊點的位置換為相對比例位置作為正規化處理。在正規化後的點群中比對是否有相同曲率變化的點，再以這些點與其相鄰點之相對距離計算出比值，用這些比值的加總作為相似度。以此方式計算的相似度進行排名，來找出最相似的圖像。測試圖庫是使用縮放圖像的方式產生不同大小的圖像，其大小範圍為0.2至3.0倍。
本論文提出之方法只需要有圖像即可運作，可以避免標籤為基礎的圖像檢索所需要的大量人力問題，以及抄襲圖像檢測的標準化。如果配合網路爬蟲程式，主動找尋網路上的圖像，則成為自動化的抄襲圖像檢測系統。

關鍵字

以圖像內容為基礎的圖像檢索 ； 數位版權管理 ； 曲率範圍空間 ； 影像抄襲

並列摘要

This study proposes an effective method for image retrieval in case that images are magnified or reduced. In contrast to the conventional keyword-based approach, the method makes use of image shapes. We determine interested points in the curvature-scale space (CSS) to recognize similar image objects. Images are processed in which edges are first extracted from original images and, then, corners are determined by the change of curvature along the edge. The corners are connected as vectors. Relative positions of the corners are determined by transposition and normalization. Based on these corners, we select the corners with similar curvature and calculate their relative distance. Similarity of two images is then the summation of the proportion of all relative distances. Similarities among images are ranked to determine which image is most relevant for a given image. To evaluate the effectiveness of the method, we use an image magnified by a factor from 0.2 to 3.0. The proposed method incorporated with a web crawler is expected to realize an automated image recognizer.

並列關鍵字

DRM ； CSS ； Image Plagiarism ； CBIR

參考文獻

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