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Content-Based Image Retrieval System By Multi-Dimensional Feature Vectors

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This paper introduces our approach to content-based image retrieval by means of key image in place of keywords. The color, spatial frequency, and shape features are extracted from the image sources and spanned in multi-dimensional feature vector space. The mutual color distances between segmented key color areas are compared to narrow the candidates for key image with desired color-tone. The spatial frequency features are represented by the limited DCT components, where low-to-middle frequency spectra are selected in circular zonal sectors. Here the mutual correlations were taken for only 7 DCT components to discriminate the differences in image textures. In addition, the compositional or shape features are simply extracted by down sampling and labeling process. The correlation between the mosaic bi-level patterns after down sampling was very useful to find the rough similarity in image structure. The paper presents experiments on the stamp or facial image retrieval.
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Document Type: Research Article

Publication date: January 1, 2003

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  • For more than 30 years, IS&T's series of digital printing conferences have been the leading forum for discussion of advances and new directions in 2D and 3D printing technologies. A comprehensive, industry-wide conference that brings together industry and academia, this meeting includes all aspects of the hardware, materials, software, images, and applications associated with digital printing systems?particularly those involved with additive manufacturing and fabrication?including bio-printing, printed electronics, page-wide, drop-on-demand, desktop and continuous ink jet, toner-based systems, and production digital printing, as well as the engineering capability, optimization, and science involved in these fields. In 2016, the conference changed its name formally to Printing for Fabrication to better reflect the content of the meeting and the evolving technology of printing.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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