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| 折扣與優(yōu)惠：團(tuán)購(gòu)最低可5折優(yōu)惠 - 了解詳情 | 論文格式：Word格式(*.doc) |  |
摘要:近年來(lái)，隨著互聯(lián)網(wǎng)高速發(fā)展，網(wǎng)上的圖片信息急劇增加，這些數(shù)據(jù)信息大都以圖像為主。如何有效地組織、管理和檢索大規(guī)模的圖像數(shù)據(jù)已成為迫切需要解決的問(wèn)題。于是基于顏色的圖像檢索作為一個(gè)嶄新的研究領(lǐng)域呈現(xiàn)在人們面前。 基于顏色的圖像檢索技術(shù)的應(yīng)用使管理者從大量的、單調(diào)的人工管理工作中解放出來(lái)，能夠方便、快速、準(zhǔn)確的從圖像數(shù)據(jù)庫(kù)中查找特定圖像。CBIR技術(shù)的核心是表示圖像顏色的特征，而顏色特征計(jì)算簡(jiǎn)單，性質(zhì)穩(wěn)定，作為圖像的一種重要視覺(jué)信息，在中已得到廣泛應(yīng)用。本文介紹了一種基于顏色特征的圖像檢索技術(shù)研究方法。 本系統(tǒng)通過(guò)將基于改進(jìn)的加權(quán)的局域顏色直方圖的圖像檢索方法和全局直方圖的圖像檢索方法相結(jié)合，提高查全率和查準(zhǔn)率。其中，基于分塊局域直方圖的檢索方法利用了圖像中間部分的重要性，將圖像平均劃分成若干個(gè)子塊，取中間一塊的圖像，計(jì)算其與參考位圖相應(yīng)位置的顏色特征距離，再計(jì)算原圖的顏色直方圖與參考位圖的顏色特征距離，分別賦予權(quán)值后得出的值就是圖像之間顏色的相似程度。本文引入歐氏距離的相似性度量方法實(shí)現(xiàn)圖像檢索。實(shí)驗(yàn)表明，該方法具有較好的查全率和查準(zhǔn)率。 關(guān)鍵詞 ：圖片檢索；網(wǎng)絡(luò)數(shù)據(jù)；顏色直方圖；幾何距離
Abstract:In recent years, with the rapid development of Internet, online picture information increased dramatically, these data are mostly based on the image. How to effectively organize, manage, and retrieve large amounts of image data has become an urgent problem to be solved. Therefore, based on color image retrieval, presenting in front of people a new field of study. Color image retrieval based on a lot of tedious manual management from freed, enables managers to find a particular image, convenient, fast and accurately from the image database. Wherein said image content, a simple, stable color characteristics, has been widely used as an important visual image information of CBIR core technology inch paper describes a method of color-based image retrieval. The system is weighted by improving local color histogram-based image retrieval method based on global image retrieval method to improve the combination of recall and precision. Characterized in that the block retrieval method based on local histogram, using the image of the intermediate portion of the importance of the average image is divided into a plurality of sub-blocks, take the middle piece of the corresponding position in the bitmap image color characteristic distance calculated with reference to the original color histogram and color characteristics of the reference bitmap from the calculation of the weights were given the value obtained was the degree of similarity between the images. This article describes the Euclidean distance similarity measure for image retrieval. Experiments show that the method has good recall and precision. Keywords Image retrieval network data color histogram geometric distance |
