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Development of expert system for extraction of the objects of interest

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Title: Development of expert system for extraction of the objects of interest
Authors: Kang, Seon-Do1 ksd2401@hanmail.net, Park, Sang-Sung1 hanyul@korea.ac.kr, Yoo, Hun-Woo2 paulyhw@yonsei.ac.kr, Shin, Young-Geun1 toctop@korea.ac.kr, Jang, Dong-Sik1 jang@korea.ac.kr
Source: Expert Systems with Applications. Apr2009 Part 2, Vol. 36 Issue 3, p7210-7218. 9p.
Subjects: Expert computer system software, Automatic extracting (Information science), Algorithm research, Optical images, Physiological effects of color, Visual perception testing
Abstract: Abstract: A new algorithm for automatic extraction of interesting objects is proposed in this paper. The proposed algorithm can be summarized in two steps. First, segmentation of color image discriminating interesting objects and backgrounds is performed. According to the research stating, ‘humans perceive things by contracting them into three to four essential colors,’ a color image is segmented into three regions utilizing k-mean algorithm, followed by the merger of the regions performed when their similarities exceeds the critical value that is drawn from the calculation of the histogram similarity. Second, identifying an interesting object out of the segmented image, generated upon the image composition theory, is performed. To have a good picture, it is important to adjust positions of interesting objects as the picture composition theory. Extracting objects is a retro-deduction process using a weighted mask based on the triangular composition of picture. To show merits of the proposed method, experiments are conducted over 400 images in comparison with recently proposed k-means connectivity constraint and graph-based image segmentation methods. [Copyright &y& Elsevier]
Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 36301427
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Development of expert system for extraction of the objects of interest
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  Data: <searchLink fieldCode="AR" term="%22Kang%2C+Seon-Do%22">Kang, Seon-Do</searchLink><relatesTo>1</relatesTo><i> ksd2401@hanmail.net</i><br /><searchLink fieldCode="AR" term="%22Park%2C+Sang-Sung%22">Park, Sang-Sung</searchLink><relatesTo>1</relatesTo><i> hanyul@korea.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Yoo%2C+Hun-Woo%22">Yoo, Hun-Woo</searchLink><relatesTo>2</relatesTo><i> paulyhw@yonsei.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Shin%2C+Young-Geun%22">Shin, Young-Geun</searchLink><relatesTo>1</relatesTo><i> toctop@korea.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Jang%2C+Dong-Sik%22">Jang, Dong-Sik</searchLink><relatesTo>1</relatesTo><i> jang@korea.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22Expert+Systems+with+Applications%22">Expert Systems with Applications</searchLink>. Apr2009 Part 2, Vol. 36 Issue 3, p7210-7218. 9p.
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  Data: <searchLink fieldCode="DE" term="%22Expert+computer+system+software%22">Expert computer system software</searchLink><br /><searchLink fieldCode="DE" term="%22Automatic+extracting+%28Information+science%29%22">Automatic extracting (Information science)</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithm+research%22">Algorithm research</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+images%22">Optical images</searchLink><br /><searchLink fieldCode="DE" term="%22Physiological+effects+of+color%22">Physiological effects of color</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+perception+testing%22">Visual perception testing</searchLink>
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  Data: Abstract: A new algorithm for automatic extraction of interesting objects is proposed in this paper. The proposed algorithm can be summarized in two steps. First, segmentation of color image discriminating interesting objects and backgrounds is performed. According to the research stating, ‘humans perceive things by contracting them into three to four essential colors,’ a color image is segmented into three regions utilizing k-mean algorithm, followed by the merger of the regions performed when their similarities exceeds the critical value that is drawn from the calculation of the histogram similarity. Second, identifying an interesting object out of the segmented image, generated upon the image composition theory, is performed. To have a good picture, it is important to adjust positions of interesting objects as the picture composition theory. Extracting objects is a retro-deduction process using a weighted mask based on the triangular composition of picture. To show merits of the proposed method, experiments are conducted over 400 images in comparison with recently proposed k-means connectivity constraint and graph-based image segmentation methods. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=36301427
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        Value: 10.1016/j.eswa.2008.09.062
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      – Code: eng
        Text: English
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        PageCount: 9
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      – SubjectFull: Expert computer system software
        Type: general
      – SubjectFull: Automatic extracting (Information science)
        Type: general
      – SubjectFull: Algorithm research
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      – SubjectFull: Optical images
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      – SubjectFull: Physiological effects of color
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      – SubjectFull: Visual perception testing
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      – TitleFull: Development of expert system for extraction of the objects of interest
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            NameFull: Kang, Seon-Do
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            NameFull: Park, Sang-Sung
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            NameFull: Yoo, Hun-Woo
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            NameFull: Shin, Young-Geun
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              Text: Apr2009 Part 2
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              Y: 2009
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