Filtering method for image retrieval based on lower bound of euclidean distance

Kohei Inoue; Kiichi Urahama

doi:10.3169/itej.59.1701

Filtering method for image retrieval based on lower bound of euclidean distance

Research output: Contribution to journal › Article › peer-review

Abstract

An acceleration method is presented for searching for similar images based on the lower bound of the Euclidean distance between feature vectors. The lower bound is calculated with lower dimensional feature vectors that are obtained by partitioning each image into several blocks. The effectiveness of the proposed method was determined experimentally using a simple image database. The time required for a 10-NN search was reduced by 95 percent on average.

Original language	English
Pages (from-to)	1701-1704
Number of pages	4
Journal	Kyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers
Volume	59
Issue number	11
DOIs	https://doi.org/10.3169/itej.59.1701
Publication status	Published - Nov 2005

All Science Journal Classification (ASJC) codes

Media Technology
Computer Science Applications
Electrical and Electronic Engineering

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title = "Filtering method for image retrieval based on lower bound of euclidean distance",

abstract = "An acceleration method is presented for searching for similar images based on the lower bound of the Euclidean distance between feature vectors. The lower bound is calculated with lower dimensional feature vectors that are obtained by partitioning each image into several blocks. The effectiveness of the proposed method was determined experimentally using a simple image database. The time required for a 10-NN search was reduced by 95 percent on average.",

author = "Kohei Inoue and Kiichi Urahama",

year = "2005",

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AU - Urahama, Kiichi

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AB - An acceleration method is presented for searching for similar images based on the lower bound of the Euclidean distance between feature vectors. The lower bound is calculated with lower dimensional feature vectors that are obtained by partitioning each image into several blocks. The effectiveness of the proposed method was determined experimentally using a simple image database. The time required for a 10-NN search was reduced by 95 percent on average.

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Filtering method for image retrieval based on lower bound of euclidean distance

Abstract

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