第五章 結論與未來研究方向
5.2 未來研究方向
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立 政 治 大 學
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第五章
結論與未來研究方向
5.1 結論
在本論文中，我們所提出的多張影像內容檢索影像內容搜尋擷取技術有不錯的成果，
藉由將人際關係所產生之網路圖的概念，以此想法建立影像關係網路，距離近的影像表 示其相似性越高，反之距離遠的影像表示其相似性較低，將 Community-Search Algorithm 應用於多張影像搜尋，找出相似影像出來。
我們的影像搜尋方法與一般影像搜尋不同的特色如下：
(1) 建立影像關係網路。
(2) 利用 Community-Search Algorithm 的技術融合社群的概念應用在圖片搜尋。
(3) 多張影像查詢。
在多張影像搜尋上，回傳影像以人類視覺主觀觀察，發現回傳影像和查詢影像有不 錯的相似度及關聯性，而以客觀數據測試結果準確度也不錯，顯示在多張影像搜尋結果 效果頗佳。
5.2 未來研究方向
在本論文中所提出一個有效的多張影像內容檢索和搜尋方法，由於傳統影像搜尋都 著重於影像特徵的抽取和比對，我們將影像特徵和影像關係整合為一個影像關係網路，
藉由演算法將影像與影像之間相關聯的影像抓取出來且有不錯的效果。
現在是網路與數位科技蓬勃發展的世代，資料以極快的速度在成長，尤以多媒體資
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訊為大宗，如何有效率且精確的搜尋出使用者所需要的影像是一個很重要的課題，傳統 影像搜尋皆著重在影像關鍵字的搜尋，進階則是以影像相關特徵值找出相似的影像，不 管傳統或進階影像搜尋皆是以單張圖片為搜尋來源，很少人提出多張影像搜尋的方法，
本文提出一個應用在多張影像搜尋的方法，結合影像特徵值搜尋已有不錯的效果，顯示 藉由影像特徵值相似度建立影像關係網路有不錯的成果，未來如果能提升影像特徵值擷 取及相似度計算的效率，則應用於影像線上搜尋會更加完美。
影像關係網路目前以影像特徵值為判斷影像彼此關係的依據，未來如果能加上語意 的關係，並讓使用者針對回傳的圖片勾選概念相符合的相關圖片後，回饋給系統，系統 再藉由回饋資訊做配對調整，對於影像搜尋結果會更加準確且符合人類對於影像的想法 及描述，使影像搜尋的使用能越來越貼近人的口語形容和人性化，長程目標未來可以進 階為延伸至音樂、視訊影像搜尋。
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