近年來，多數研究皆以內容為基礎作影像搜尋，而這些研究多利用影像內容特徵的比對，希望透過相似函數的計算，直接找出相類似的比對影像的特徵，且有效率地擷取資料。雖然某些以內容為基礎的影像搜尋系統也許能提供不錯的擷取結果，但是這些低階的影像內容特徵並不能完全反映人類高階語意概念，事實上，這些隱藏在圖片裡的人性概念，才是影像擷取真正的關鍵目標。本研究主要目的係以影音多媒體內容為基礎，透過物件的註解方式，發展以語意概念為導向之智慧型影像內容搜尋方法，並利用資料探勘相關技術，提供使用者透過人性化的介面以捕捉更高階的人性概念。我們將此嶄新的方法稱之為智慧型概念導向式影像內容搜尋擷取(Intelligent Concept-Oriented Search for Content-based Image Retrieval)。在此方法中，我們發展了以下的創新技術:1)智慧型的影像內容搜尋方法2 )物件式的註解方法3)物件式的關聯探勘技術4)語意概念之排序方法。

In recent years, a number of research works have been proposed for content-based image retrieval with different features. Theses works usually use the content of images, low-level features to calculate the similarity between images that hope to find the similar images and retrieve image database efficiently. Although some novel content-based image retrieval systems may provide good retrieval results, the low-level features cannot entirely represent the high-level human sense in retrieval. Hence, the retrieval process is not effective. In fact, the concepts hidden in the images are often the key targets for image retrieval from the viewpoint of human sense. In this paper, we propose a new approach named Intelligent Concept-Oriented Search (ICOS) that can catch the high-level concepts of the users for performing content-based image retrieval by using a data mining approach. Through experimental evaluation, the proposed approach can provide fast and accurate image retrieval in user-friendly interface. We also develop new skills like the methods of intelligent concept-oriented search for content-based image retrieval, object annotation, association rules between objects, and the ranking methods for ontology concept.

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