【摘要】：伴隨互聯(lián)網(wǎng)技術(shù)的飛速發(fā)展,媒體產(chǎn)業(yè)積累的數(shù)字資產(chǎn)越來越多,媒體資源管理(DAM)成為媒體行業(yè)的一個(gè)研究熱點(diǎn)。作為媒體資源管理的一個(gè)重要功能,基于內(nèi)容的多媒體內(nèi)容檢索逐漸應(yīng)用到DAM系統(tǒng)中。如何綜合利用提取到的媒體素材的低層特征,獲得更好的檢索效果?針對(duì)這個(gè)問題,本文提出了一種融合全局特征和局部特征的特征融合模型,利用不同特征各自的優(yōu)勢,在此基礎(chǔ)上設(shè)計(jì)并實(shí)現(xiàn)了檢索效果優(yōu)化的媒體資源管理系統(tǒng)。首先,本文以圖像為例,研究了基于內(nèi)容的圖像檢索中與圖像特征提取的相關(guān)問題,提出了一種融合圖像局部特征和全局特征的檢索方法,其中局部特征以基于SIFT描述子的詞袋模型對(duì)圖像特征進(jìn)行描述,全局特征以圖像的顏色空間為例對(duì)圖像進(jìn)行描述,將該方法在Corel1000圖像檢索測試數(shù)據(jù)集上進(jìn)行試驗(yàn)。實(shí)驗(yàn)表明,圖像特征融合對(duì)于系統(tǒng)的整體檢索準(zhǔn)確率有一定提高。然后,本文對(duì)現(xiàn)有的DAM系統(tǒng)進(jìn)行了對(duì)比研究,在充分考慮系統(tǒng)的擴(kuò)展性、開放性以及靈活性等設(shè)計(jì)原則的基礎(chǔ)上,通過分析系統(tǒng)功能模塊和資產(chǎn)數(shù)據(jù)結(jié)構(gòu)設(shè)計(jì)了 DAM系統(tǒng),最后利用J2EE、MongoDB等技術(shù)實(shí)現(xiàn)了系統(tǒng),完成了對(duì)系統(tǒng)檢索功能的測試以及對(duì)測試結(jié)果的分析。通過對(duì)檢索優(yōu)化DAM系統(tǒng)的檢索測試結(jié)果證實(shí)其適用性和可靠性。
文內(nèi)圖片：
圖片說明：圖２－ｌ邋ＨＳＶ顏色空間［２４】逡逑
[Abstract]:With the rapid development of Internet technology, more and more digital assets are accumulated in the media industry. Media resource management (DAM) has become a research hot spot in the media industry. As an important function of media resource management, content-based multimedia content retrieval is gradually applied to DAM system. How to make comprehensive use of the low-level features of the extracted media materials to obtain better retrieval results? In order to solve this problem, a feature fusion model combining global features and local features is proposed in this paper. Based on the advantages of different features, a media resource management system with optimal retrieval effect is designed and implemented. Firstly, taking the image as an example, this paper studies the problems related to image feature extraction in content-based image retrieval, and proposes a retrieval method for fusion image local features and global features, in which the local features describe the image features with the word bag model based on SIFT descriptor, and the global features take the color space of the image as an example to describe the image, and the method is tested on the Corel1000 image retrieval test data set. The experimental results show that the image feature fusion can improve the overall retrieval accuracy of the system to a certain extent. Then, this paper makes a comparative study of the existing DAM system. On the basis of fully considering the design principles of expansibility, openness and flexibility of the system, the DAM system is designed by analyzing the functional modules and asset data structure of the system. Finally, the system is realized by using J2EE, MongoDB and other technologies, and the test of the retrieval function of the system and the analysis of the test results are completed. The applicability and reliability of the retrieval optimization DAM system are verified by the retrieval test results.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41;TP311.52

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