文章基本信息

标题：Discovering Robustness Amongst CBIR Features
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作者：Brandeis Marshall
期刊名称：International Journal of Web & Semantic Technology
印刷版ISSN：0976-2280
电子版ISSN：0975-9026
出版年度：2012
卷号：3
期号：2
DOI：10.5121/ijwest.2012.3202
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Digital photography faces the challenges of image storage, retrieval and provenance at the consumer and commercial level. One major obstacle is in the computational cost of image processing. Solutions range from using high-throughput computing systems to automatic image annotation. Consumers can not dedicate computing systems to image processing and handling nor do consumers have large-scale image repositories to make automatic image annotation effective. Nevertheless, we consider an alternative approach: reducing computational cost in image processing. Using a 25,000 image collection, we consider using a sub- set of image features to evaluate image similarity. We discover several robust features displaying comparable relevancy performance with the additional benefit of reduced processing cost.