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Image Search System with Automatic Weighting Mechanism for Selecting Features

Barakbah, Ali Ridho and Kiyoki, Yasushi (2010) Image Search System with Automatic Weighting Mechanism for Selecting Features. In: The 6th International Conference on Information and Communication Technology and Systems (ICTS) 2010, 28 Sep 2010, Surabaya, Indonesia.

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    Abstract

    This paper presents an easy-to-use and highly precise image search system. The key technology of the system is an automatic weighting mechanism for selecting features based on combining color, shape and structure features. Generally, the users should consider and determine weights for features to represent their preferences for selecting the features of an image search. These conventional systems make difficult for the novice users because it needs technical consideration for r e t r i e va l s y s t e m . Th i s p a p e r pr o p o s e s a n e w mechanism of automatic weighting for selecting the features by anal yzing the distribution of color information to determine representative features. The color moments of the image are extracted and manipulated to calculate the color distance, the texture density and the shape property to determine respectively color, structure and shape weights. The color distances are calculated from the first order color moment by applying the shape independent clustering in order to construct and calculate distances of color hierarchy. The texture density is calculated from the second order of color moment to be more sensitive to scene the structures of images. The shape property is obtained from the third order of color moments. This proposed image search system is evaluated with a image retrieval benchmark dataset from Wang image collections. The experimental results clarify effectiveness of the proposed image search system to ease the feature selection and to reach the highly-retrieval precision with designated weights from the automatic weighting mechanism proposed in this paper.

    Item Type: Conference or Workshop Item (Paper)
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
    Depositing User: Dr. Ali Ridho Barakbah
    Date Deposited: 22 Mar 2015 12:17
    Last Modified: 22 Mar 2015 12:17
    URI: http://repo.pens.ac.id/id/eprint/2736

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