Distributed dynamic mean shift algorithm for image segmentation

Kohei Inoue; Kiichi Urahama

doi:10.3169/itej.61.1614

Distributed dynamic mean shift algorithm for image segmentation

Kohei Inoue, Kiichi Urahama

Visual Communication Design

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

Abstract

A fast and memory-efficient method has been created for the dynamic mean shift (DMS) algorithm, which is an iterative mode-seeking algorithm. Running the standard DMS algorithm requires a large amount of memory because the algorithm dynamically updates all data during iterations. Therefore, it is difficult to use a conventional DMS algorithm for clustering large dataset. This difficulty is overcome by partitioning a dataset into subsets, and the resultant procedure is called a "distributed DMS algorithm", Experimental results on image segmentation show that the distributed DMS algorithm requires less memory than that of the conventionally used DMS algorithm.

Original language	English
Pages (from-to)	1614-1620
Number of pages	7
Journal	Kyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers
Volume	61
Issue number	11
DOIs	https://doi.org/10.3169/itej.61.1614
Publication status	Published - Nov 2007

All Science Journal Classification (ASJC) codes

Media Technology
Computer Science Applications
Electrical and Electronic Engineering

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