近年來，隨著數位科技快速的發展，影像資料量迅速的增加，因此影像檢索成為重要的多媒體技術之一。在傳統的影像內容檢索技術中，使用影像低階特徵值，例如顏色(Color)、紋理(Texture)、形狀(Shape)等來描述影像的內容並進行圖片相似度的比對。然而，傳統的影像內容檢索僅提供單張影像查詢，很少研究多張影像的查詢。因此，本研究提出一個可針對多張影像查詢的方法以提供多張影像查詢的影像內容檢索。本研究將影像內容檢索結合社群網絡演算法，使用MPEG-7中相關特徵描述子和SIFT做為主要特徵向量，擷取影像的低階影像特徵，透過特徵相似度計算建立影像之間的網絡，並利用社群網絡演算法找出與多張查詢影像相似的影像。實驗結果顯示所提出的方法可精確的擷取到相似的影像。 / In recent years, with the faster and faster development of computer technology, the number of digital images is grown rapidly so that the Content-Based Image Retrieval has become one of important multimedia technologies. Much research has been done on Content-Based Image Retrieval. However, little research has been done on query by multiple images. This thesis investigates the mechanism for query by multiple images. First, MPEG-7 image features and SIFT are extracted from images. Then, we calculate the similarity of images to construct the proximity graph which represents the similarity structure between images. Last, processing of query by multiple images is achieved based on the social network algorithms. Experimental results indicate the proposed method provides high accuracy and precision.