在多媒體的網路世界裡，電腦若能對影像能有更深入的了解，將會有很大的進步。本篇論文對影像上結合了低階層技術和高階層技術，並導入本體論，使系統可以對影像有更深入的理解，成為一個更智慧的系統。
本篇論文的主要目標為「使系統了解影像」，將低階層架技術和高階層技術的結合，並且導入本體論的概念，是本篇論文的研究重點，並設計一個影像擷取系統實作，來測試本論文所提出來的方法。此系統利用了低階層架構中的自動辨識技術，高階層架構中的自然語言處理技術，導入本體論裡的推論機制，並且加入了學習機制，利用這些技術來整合出本篇論文裡的系統。藉由這些技術整合，可以使系統可以對影像有更進一步的理解，在未來的將會有更廣泛的應用。
本篇論文利用不同實驗的方法，來測試此影像擷取系統的特性，包含有推論、學習和多模式搜尋方式，實驗的結果可以顯示在有推論機制的系統裡，所能逹到的效能；且在有學習機制下，在不同的物件數下，會對搜尋造成什麼影響；且本篇論文是結合低階層架構和高階層架構，所以在搜尋的方式也結合起來，不僅只有文字或影像，此系統可以接受二種不同模式的搜尋方式。

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