本文選題：基于內(nèi)容的圖像檢索 + beamlet分析�。� 參考：《河北師范大學(xué)》2013年碩士論文

【摘要】：近幾十年來，隨著互聯(lián)網(wǎng)的普及和數(shù)字圖像處理技術(shù)的成熟，基于內(nèi)容的圖像檢索成為信息時(shí)代的研究熱點(diǎn)．互聯(lián)網(wǎng)上設(shè)計(jì)圖的數(shù)量大量增加，如服裝設(shè)計(jì)圖、提包設(shè)計(jì)圖、首飾設(shè)計(jì)圖，還有卡通設(shè)計(jì)圖等等，為了合法的保護(hù)設(shè)計(jì)師的知識(shí)產(chǎn)權(quán)，方便高效的進(jìn)行設(shè)計(jì)圖檢索成為基于內(nèi)容的圖像檢索的重要應(yīng)用前景之一．實(shí)際得到的圖像常常會(huì)受到噪聲污染，或人為或圖像傳輸設(shè)備造成，因此抗干擾的設(shè)計(jì)圖檢索的研究是必要的． 本文的主要工作是：首先，對多尺度幾何分析—beamlet分析進(jìn)行了深入研究，詳細(xì)介紹了beamlet基本理論．目前為止從查閱的文獻(xiàn)看，只有對beamlet算法結(jié)果的描述，而沒有對算法的具體實(shí)現(xiàn)步驟作系統(tǒng)的闡述，，本文的重點(diǎn)是給出了beamlet算法—無結(jié)構(gòu)算法和樹結(jié)構(gòu)算法的具體實(shí)現(xiàn)步驟． 其次，用beamlet算法實(shí)現(xiàn)了強(qiáng)噪聲下弱信號(hào)的提取，在高斯噪聲、瑞利噪聲和周期噪聲中都能很好的恢復(fù)幾乎完整的原直線的存在方式；同時(shí)還用beamlet算法實(shí)現(xiàn)了圖像線特征的多尺度描述和圖像區(qū)域的提取． 最后，也即本文重點(diǎn)，在基于內(nèi)容的圖像檢索中，尤其是設(shè)計(jì)圖檢索，提出了beamlet特征，無論圖像含不含噪聲，beamlet算法可直接提取圖像的線特征，不需要對圖像降噪預(yù)處理．本文初步實(shí)現(xiàn)了基于beamlet的圖像檢索，檢索結(jié)果表明基于beamlet的抗干擾的設(shè)計(jì)圖檢索的有效性，為beamlet變換的應(yīng)用擴(kuò)展了一個(gè)新方向．
[Abstract]:In recent decades, with the popularity of the Internet and the maturity of digital image processing technology, content-based image retrieval has become a research hotspot in the information age. The number of designs on the Internet has increased substantially, such as clothing drawings, bag drawings, jewelry drawings, cartoon designs, etc., in order to legally protect the intellectual property rights of designers, Convenient and efficient design map retrieval is one of the important applications of content-based image retrieval. The actual images are often polluted by noise or caused by artificial or image transmission equipment, so it is necessary to study the anti-jamming design map retrieval. The main work of this paper is as follows: firstly, the multi-scale geometric analysis -Beamlet analysis is deeply studied, and the basic theory of beamlet is introduced in detail. So far, only the description of the results of the beamlet algorithm, but not the detailed implementation steps of the algorithm is described. The emphasis of this paper is to give the implementation steps of the beamlet algorithm, the unstructured algorithm and the tree structure algorithm. Secondly, beamlet algorithm is used to extract the weak signal under strong noise. In Gao Si noise, Rayleigh noise and periodic noise, the almost complete original line can be recovered. At the same time, the beamlet algorithm is used to realize the multi-scale description of image line features and the extraction of image region. Finally, that is the focus of this paper, in the content-based image retrieval, especially the design image retrieval, the beamlet feature is proposed. Regardless of whether the image contains noiseless features, the line feature of the image can be extracted directly without the need of image de-noising preprocessing. In this paper, the image retrieval based on beamlet is preliminarily implemented. The retrieval results show that the anti-jamming design map retrieval based on beamlet is effective, which extends a new direction for the application of beamlet transform.
【學(xué)位授予單位】：河北師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前2條

1 郭蔚;李婷;;輪廓波變換原理及其構(gòu)造方法[J];數(shù)學(xué)進(jìn)展;2012年03期

2 章毓晉,徐寅,劉忠偉,姚玉榮,李R

本文編號(hào)：1856013