Speed-up Multi-modal Near Duplicate Image Detection

作     者：Chunlei Yang Jinye Peng Jianping Fan 

作者机构：1CSIRO Sustainable Ecosystems Carmody Road St. Lucia Queensland Australia 2CSIRO Sustainable Ecosystems Highett Australia CSIRO Sustainable Ecosystems Highett Australia 

出 版 物：《Open Journal of Applied Sciences》 (应用科学（英文）)

年 卷 期：2013年第3卷第1期

页      面：16-21页

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Near-Duplicate Detection Coarse-To-Fine Framework Multi-Modal Feature Integration 

摘      要：Near-duplicate image detection is a necessary operation to refine image search results for efficient user exploration. The existences of large amounts of near duplicates require fast and accurate automatic near-duplicate detection methods. We have designed a coarse-to-fine near duplicate detection framework to speed-up the process and a multi-modal integra-tion scheme for accurate detection. The duplicate pairs are detected with both global feature (partition based color his-togram) and local feature (CPAM and SIFT Bag-of-Word model). The experiment results on large scale data set proved the effectiveness of the proposed design.