本文選題：網上購物 + 視覺圖像檢索�。� 參考：《大連理工大學》2013年碩士論文

【摘要】：隨著網上購物的快速發(fā)展,網絡上出現(xiàn)百萬張,甚至上億張的不同類別的商業(yè)商品圖片。傳統(tǒng)的基于關鍵字的搜索引擎已經逐漸不能滿足用戶的需要。如何有效的利用視覺搜索手段來提供給用戶精確度高、方便快捷的可視化搜索引擎目前仍然是一個重要的,富有挑戰(zhàn)性的任務。在圖像檢索領域,詞袋模型被廣泛應用,結合倒排文件索引方法索引和檢索數(shù)據(jù)庫圖像能夠大大減少匹配中的候選圖像數(shù)目,實現(xiàn)更有效的響應�；谠~袋模型的搜索圖像檢索中忽略了點特征之間的空間關系以及邏輯關系,降低了一定的檢索準確性。本文中,我們在詞袋模型的基礎上,結合點特征SIFT與區(qū)域特征MSER的不同特性,得到具有更好表達性的視覺詞匯,以及在空間和邏輯上有緊密關系的圖像的視覺短語。在文中,我們將在MSER區(qū)域內頻繁出現(xiàn)的SIFT特征對即認為兩個特征之間具有緊密關系,記為視覺短語。在完成整幅圖像的全局特征匹配前提下,考慮到用戶在購買商品時不僅會對商品的顏色,質地等因素有特別要求,同時也會對局部的設計感興趣,針對這一點,我們提出同時提取圖像的顏色、紋理等特征,并加入用戶交互功能,以提供用戶標注感興趣區(qū)域的接口,進而實施系統(tǒng)對查詢圖像局部區(qū)域的第二階段匹配,最后兩階段檢索結果融合以提高檢索精度。在實驗評估部分,我們檢驗了利用本文提出的方法來實現(xiàn)的檢索系統(tǒng)的實驗結果。分別通過全局匹配,和局部匹配方法,對多次實驗結果進行比較,驗證了視覺短語和交互階段局部匹配方法的有效性和必要性。
[Abstract]:With the rapid development of online shopping, there are millions, even hundreds of millions of pictures of different categories of commercial goods on the Internet. Traditional keyword-based search engines have been unable to meet the needs of users. How to effectively use visual search methods to provide users with high accuracy, convenient and fast visual search engine is still an important and challenging task. In the field of image retrieval, word bag model is widely used. Indexing and retrieving database images with inverted file indexing method can greatly reduce the number of candidate images in matching and achieve a more effective response. In the search image retrieval based on the word bag model, the spatial and logical relations between the points are ignored, and the retrieval accuracy is reduced. In this paper, on the basis of the lexical bag model, we combine the different characteristics of sift and MSER, and obtain visual words with better expression, and visual phrases of images closely related in space and logic. In this paper, the sift feature pairs, which occur frequently in the MSER region, are considered to be closely related to each other as visual phrases. On the premise of completing the global feature matching of the whole image, considering that the user will not only have special requirements for the color, texture and other factors of the product, but also be interested in the local design, in view of this, We propose to extract the color, texture and other features of the image at the same time, and add the user interaction function to provide the interface for the user to annotate the region of interest, and then implement the second stage matching of querying the local region of the image. In order to improve the retrieval accuracy, the final two stages of retrieval results fusion. In the part of experimental evaluation, we verify the experimental results of the retrieval system implemented by the method proposed in this paper. Through global matching and local matching, the experimental results are compared to verify the validity and necessity of visual phrases and interactive local matching.
【學位授予單位】：大連理工大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP391.41

【參考文獻】

相關期刊論文 前1條

1 曾巒;翟優(yōu);譚久彬;;基于SIFT的自動匹配策略[J];光電工程;2011年02期

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本文編號：2052804