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A UNIFIED FRAMEWORK FOR SIMILARITY CALCULATION BETWEEN IMAGES
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@MISC{Kushki_aunified,
author = {Azadeh Kushki and Panagiotis Androutsos and Konstantinos N. Plataniotis and Anastasios N. Venetsanopoulos},
title = {A UNIFIED FRAMEWORK FOR SIMILARITY CALCULATION BETWEEN IMAGES},
year = {}
}
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Abstract
Emergence of large digital visual data repositories motivates the need for effective indexing and retrieval tools. In traditional approaches, similarity among two images is a weighted distance between two feature vectors. These techniques, however, do not provide enough flexibility in modelling user queries. This paper proposes a framework where image similarities are obtained through a decision making process using fuzzy theory. The analysis and results of this paper indicate that the aggregation technique presented here provides an effective, general, and flexible tool for similarity calculation based on the combination of individual descriptors and features. 1.
Keyphrases
unified framework similarity calculation image individual descriptor large digital visual data repository retrieval tool feature vector weighted distance aggregation technique flexible tool user query fuzzy theory effective indexing decision making process enough flexibility image similarity similarity calculation traditional approach paper indicate
