Region segmentation using K-mean clustering and genetic algorithms

Y. Horita; T. Murai; M. Miyahara

doi:10.1109/ICIP.1994.413691

Region segmentation using K-mean clustering and genetic algorithms

Y. Horita, T. Murai, M. Miyahara

Civil Design and Engineering

Research output: Contribution to journal › Conference article › peer-review

7 Scopus citations

Abstract

One of the hard problems in image recognition and understanding is region segmentation. A traditional segmentation method such as clustering is not fully useful for any image, because of the initial values of clusters and the evaluation functions of segmented clusters affect the results of region segmentation. To solve this problem, we introduce the genetic algorithm (GA) for clustering. The experimental result shows the satiable results of region segmentation which have been achieved by applying GA.

Original language	English
Article number	413691
Pages (from-to)	1016-1020
Number of pages	5
Journal	Proceedings - International Conference on Image Processing, ICIP
Volume	3
DOIs	https://doi.org/10.1109/ICIP.1994.413691
State	Published - 1994
Event	The 1994 1st IEEE International Conference on Image Processing - Austin, TX, USA Duration: 1994/11/13 → 1994/11/16

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Signal Processing

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10.1109/ICIP.1994.413691

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title = "Region segmentation using K-mean clustering and genetic algorithms",

abstract = "One of the hard problems in image recognition and understanding is region segmentation. A traditional segmentation method such as clustering is not fully useful for any image, because of the initial values of clusters and the evaluation functions of segmented clusters affect the results of region segmentation. To solve this problem, we introduce the genetic algorithm (GA) for clustering. The experimental result shows the satiable results of region segmentation which have been achieved by applying GA.",

author = "Y. Horita and T. Murai and M. Miyahara",

note = "Publisher Copyright: {\textcopyright} 1994 IEEE.; The 1994 1st IEEE International Conference on Image Processing ; Conference date: 13-11-1994 Through 16-11-1994",

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AU - Horita, Y.

AU - Murai, T.

AU - Miyahara, M.

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N2 - One of the hard problems in image recognition and understanding is region segmentation. A traditional segmentation method such as clustering is not fully useful for any image, because of the initial values of clusters and the evaluation functions of segmented clusters affect the results of region segmentation. To solve this problem, we introduce the genetic algorithm (GA) for clustering. The experimental result shows the satiable results of region segmentation which have been achieved by applying GA.

AB - One of the hard problems in image recognition and understanding is region segmentation. A traditional segmentation method such as clustering is not fully useful for any image, because of the initial values of clusters and the evaluation functions of segmented clusters affect the results of region segmentation. To solve this problem, we introduce the genetic algorithm (GA) for clustering. The experimental result shows the satiable results of region segmentation which have been achieved by applying GA.

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U2 - 10.1109/ICIP.1994.413691

DO - 10.1109/ICIP.1994.413691

M3 - 会議記事

AN - SCOPUS:84998577684

SN - 1522-4880

VL - 3

SP - 1016

EP - 1020

JO - Proceedings - International Conference on Image Processing, ICIP

JF - Proceedings - International Conference on Image Processing, ICIP

M1 - 413691

T2 - The 1994 1st IEEE International Conference on Image Processing

Y2 - 13 November 1994 through 16 November 1994

ER -

Region segmentation using K-mean clustering and genetic algorithms

Abstract

ASJC Scopus subject areas

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