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A Similar Image Search Engine Based on Millions of Images and Distributed Computing

Author: ZhouYuan
Tutor: BaoHuJun;HeXiaoFei
School: Zhejiang University
Course: Applied Computer Technology
Keywords: Content-based image retrieval Search engine Distributed Computing Distributed File System Image wavelet decomposition Scale-invariant image feature Local sensitive hash
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 257
Quote: 1
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Abstract


This article theory with distributed content-based image retrieval technology combine to discuss the building of a million similar magnitude image search engine . First of all , this study similar image retrieval based image retrieval , and similar images defined as two categories : overall similar images , such as the composition structure is similar to or different sizes of the same content , different quality images ; partially similar images , for example, a group of images of the same object , the same scenes or the same characters . For the two different types of similar images , respectively, using the image global features - Haar wavelet decomposition characteristics and local image characteristics - SIFT feature to be processed. Second, the goal of this paper is to build millions of orders of magnitude more than the large-scale image search engine , the storage system to be matched image features over one billion . Match for the massive high-dimensional image feature vector efficiency problem , this paper studied the pros and cons of various types of algorithms , and select local sensitive hash (Locality Sensitive Hashing, LSH) algorithm as a method of indexing and matching image features to discuss with adapt the local sensitive hash algorithm parameter selection and system implementation strategies. On the other hand , for vast amounts of image and image features in the system of data storage and computing problems , this article out of the limitations of the study , the general image retrieval using distributed storage and calculation methods to solve large-scale data storage and computing problems . The system implements a lightweight Windows platform distributed file system , and implemented based on the file system image feature extraction , and indexing and retrieval matching calculation distributed parallelism . The experimental results proved that the design of the system can successfully work in the millions of magnitude on the image database , and in practical applications can be successful and efficient handling of the similar image of the user's query . Keywords: content-based image retrieval , search engine , distributed computing , distributed file system

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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