本文選題：垂直搜索　切入點(diǎn)：圖像內(nèi)容檢索　出處：《大連海事大學(xué)》2013年博士論文　論文類型：學(xué)位論文

【摘要】：隨著網(wǎng)絡(luò)帶寬和軟硬件性能的不斷提高,多媒體文件的搜索需求日益高漲,圖像檢索作為文本檢索到媒體檢索跨域的第一步,逐漸成為是一個(gè)熱門的研究領(lǐng)域。本文針對(duì)圖像檢索領(lǐng)域,從基于圖像上下文的搜索和基于圖像內(nèi)容檢索兩方面進(jìn)行研究。 首先,研究了基于圖像上下文垂直搜索引擎中的網(wǎng)絡(luò)蜘蛛技術(shù)進(jìn)行網(wǎng)絡(luò)蜘蛛抓取和主題判定,使用DOM樹和正則表達(dá)式對(duì)采集后的信息進(jìn)行上下文提取,對(duì)提取內(nèi)容切詞建立索引,在滿足互聯(lián)網(wǎng)應(yīng)用的同時(shí),利用移動(dòng)互聯(lián)網(wǎng)技術(shù),將內(nèi)容轉(zhuǎn)化至移動(dòng)終端,并使用樹狀表示法建立規(guī)則知識(shí)庫,實(shí)現(xiàn)結(jié)果的個(gè)性化推薦。 然后,研究了基于內(nèi)容的圖像檢索技術(shù),將圖像分層分割后,提取圖像顏色、紋理和邊緣特征進(jìn)行多種特征融合,建立基于模糊支持向量機(jī)的多項(xiàng)分類模型,通過模型對(duì)圖像不同圖層的分類將多個(gè)關(guān)鍵字分配至該圖像,使圖像內(nèi)容變成多關(guān)鍵字的描述 最后,在圖像檢索的基礎(chǔ)上,提取圖像視覺內(nèi)容特征中的紋理和顏色,抓住圖像間的內(nèi)容特點(diǎn)改進(jìn)色彩傳遞方法。一方面,通過計(jì)算圖像間的紋理相似度,搜索內(nèi)容與灰度圖像相近的色源圖像,提高染色的成功率,另一方面提取顏色特征對(duì)圖像進(jìn)行更科學(xué)的像素采樣,改進(jìn)色彩傳遞算法本身,加強(qiáng)染色效果。
[Abstract]:With the improvement of network bandwidth and the performance of hardware and software, the search demand for multimedia files is increasing. Image retrieval is the first step of text retrieval to cross-domain media retrieval. This paper focuses on image retrieval from two aspects: image context-based search and image content retrieval. Firstly, the web spider technology based on image context vertical search engine is studied for web spider capture and theme determination, and DOM tree and regular expression are used to extract the context of the collected information. In order to meet the needs of Internet application, the content can be converted to mobile terminal by using mobile Internet technology, and the rule knowledge base can be established by using tree representation to realize the personalized recommendation of the result. Then, the content-based image retrieval technology is studied. After the image is segmented, the color, texture and edge features of the image are fused, and a multi-item classification model based on fuzzy support vector machine (FSVM) is established. Multiple keywords are assigned to the image by classifying the different layers of the image by the model, so that the content of the image becomes a multi-keyword description. Finally, on the basis of image retrieval, the texture and color of image visual content feature are extracted, and the color transfer method is improved by grasping the content characteristic of image. On the one hand, the texture similarity between images is calculated. In order to improve the success rate of coloring, color source images with similar contents to gray-scale images can be searched. On the other hand, color features can be extracted for more scientific pixel sampling, and the color transfer algorithm itself can be improved to enhance the effect of coloring.
【學(xué)位授予單位】：大連海事大學(xué)
【學(xué)位級(jí)別】：博士
【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10條

1 曹從軍;劉強(qiáng)s，

本文編號(hào)：1616768