Automatic decision method of parameters in the maximum distance algorithm

Koji Sakamoto, Hironobu Fukai, Takanari Tanabata, Yasue Mitsukura, Seiji Ito, Minoru Fukumi

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

The maximum distance algorithm has been considered to be effective for an image segmentation of color scenery images. However, in the maximum distance algorithm, the parameter which decides the end term of the clustering is set in advance. The applicable value of this parameter depends on the individual image. Therefore, we propose the automated adjustment method of the maximum distance algorithm's parameter for the image segmentation of scenery images. First, "image density" is defined as the measure to evaluate the complexity of each image. Image density is calculated by difference between average of color value and color value of each pixel. Then, the relation of the image density and applicable value of the maximum distance algorithm is investigated. This investigation enables us the automated adjustment method of maximum distance algorithm's parameter fitting the image density of individual image. In this paper, the computer simulation is done for the purpose of comparing the conventional method and proposed method. There is the regulation between appropriate parameter in maximum distance algorithm. The experiment with about 100 images shows the effectiveness of the proposed method.

本文言語English
ホスト出版物のタイトルICCAS 2007 - International Conference on Control, Automation and Systems
ページ785-788
ページ数4
DOI
出版ステータスPublished - 2007
イベントInternational Conference on Control, Automation and Systems, ICCAS 2007 - Seoul, Korea, Republic of
継続期間: 2007 10 172007 10 20

出版物シリーズ

名前ICCAS 2007 - International Conference on Control, Automation and Systems

Other

OtherInternational Conference on Control, Automation and Systems, ICCAS 2007
CountryKorea, Republic of
CitySeoul
Period07/10/1707/10/20

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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