本文選題：圖像檢索 + 相關(guān)反饋��； 參考：《南京郵電大學(xué)》2016年碩士論文

【摘要】：日新月異的計(jì)算機(jī)技術(shù)給人們帶來了嶄新的生活體驗(yàn)與工作方式。隨著網(wǎng)絡(luò)帶寬的增加,用戶可以更加快速的利用互聯(lián)網(wǎng)對(duì)網(wǎng)站進(jìn)行訪問,但互聯(lián)網(wǎng)中龐大的數(shù)據(jù)量也使得用戶在查詢特定消息的過程如同大海撈針。因此,一個(gè)全新的信息搜索技術(shù)“搜索引擎”應(yīng)時(shí)而生,并在短時(shí)間內(nèi)得到快速的發(fā)展和改進(jìn)。由于互聯(lián)網(wǎng)中多媒體版塊的不斷豐富,用戶對(duì)搜索內(nèi)容便有了更多的需求。其中為了滿足用戶對(duì)圖像搜索的要求,從之前發(fā)展比較成熟的基于文字的圖像搜索技術(shù),到現(xiàn)在逐漸完善的基于內(nèi)容的圖像搜索技術(shù),各種各樣基于互聯(lián)網(wǎng)圖像的搜索技術(shù)蓬勃發(fā)展。通常,用戶在搜索圖像時(shí),最為關(guān)心的便是搜索到的結(jié)果與用戶的期望值是否相符。因此本文結(jié)合了基于文字和基于內(nèi)容的搜索引擎的技術(shù)特點(diǎn),提出了基于相關(guān)反饋的搜索引擎并加以實(shí)現(xiàn)。首先介紹了圖像搜索系統(tǒng)的相關(guān)背景和研究意義,其次簡單描述了搜索系統(tǒng)要用到的關(guān)鍵技術(shù),包括鏈接爬取、內(nèi)容提取、圖像爬取、索引建立等等,以此為開發(fā)出一個(gè)完整的搜索系統(tǒng)提供了必要的理論和技術(shù)準(zhǔn)備。本文在第三章中詳細(xì)闡述了基于相關(guān)反饋的搜索引擎的框架結(jié)構(gòu),它包含用戶接口模塊、圖像處理模塊、數(shù)據(jù)爬取模塊,并在這些模塊中添加了用戶的相關(guān)反饋機(jī)制。第四章在第三章所提出的框架與流程的基礎(chǔ)上具體實(shí)現(xiàn)了相關(guān)功能。在數(shù)據(jù)搜索模塊,本文通過在爬取過程中使用HtmlUnit插件,解決了一般Spider只能爬取靜態(tài)頁面而無法解析動(dòng)態(tài)頁面的問題。在圖像處理模塊,本文在特征提取方面?zhèn)戎赜趫D像低層次特征的提取,通過使用感知哈希算法,對(duì)圖像的形狀、紋理特征以數(shù)字的形式呈現(xiàn)出來。最后通過相關(guān)測試,檢驗(yàn)了所有模塊的功能,驗(yàn)證了本文所提搜索引擎與其它搜索引擎相比具有較高的查準(zhǔn)率。本論文為實(shí)踐應(yīng)用型研究型論文,目的在于研究和實(shí)現(xiàn)基于相關(guān)反饋的圖像搜索系統(tǒng)。它在傳統(tǒng)的搜索系統(tǒng)模式之外另辟蹊徑,改進(jìn)了搜索系統(tǒng)的查準(zhǔn)率與查全率,同時(shí)還改善了用戶在搜索過程中的體驗(yàn)度。
[Abstract]:The rapid development of computer technology has brought people a new life experience and working style.With the increase of network bandwidth, users can use the Internet to visit the website more quickly, but the huge amount of data in the Internet also makes the process of searching for specific messages like looking for a needle in a haystack.Therefore, a new information search technology "search engine" came into being, and in a short period of time, rapid development and improvement.Because of the continuous enrichment of multimedia sections in the Internet, users have more demand for searching content.In order to meet the requirements of the users for image search, from the more mature text-based image search technology developed before, to the content based image search technology,All kinds of search technology based on Internet image is booming.In general, when searching for images, the most important concern is whether the results are in line with the user's expectations.Therefore, combining the technical characteristics of text and content-based search engines, this paper proposes and implements a search engine based on correlation feedback.This paper introduces the background and research significance of image search system, and then briefly describes the key technologies to be used in the search system, including link crawling, content extraction, image crawling, index building and so on.This provides the necessary theoretical and technical preparation for the development of a complete search system.In the third chapter, the framework of search engine based on correlation feedback is described in detail. It includes user interface module, image processing module, data crawling module, and the relevant feedback mechanism of users is added to these modules.The fourth chapter realizes the related functions on the basis of the framework and process proposed in the third chapter.In the data search module, this paper solves the problem that Spider can only crawl static pages but can not parse dynamic pages by using HtmlUnit plug-in during crawling.In the image processing module, this paper focuses on feature extraction in the image low-level feature extraction, through the use of perceptual hashing algorithm, image shape and texture features are presented in digital form.Finally, the functions of all modules are tested through the relevant tests, and it is verified that the search engine proposed in this paper has a higher precision than other search engines.The purpose of this paper is to study and implement an image search system based on correlation feedback.In addition to the traditional search system, it improves the precision and recall of the search system, and also improves the user's experience in the search process.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41

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