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Information Journal Paper

Title

STRUCTURE-TEXTURE IMAGE DECOMPOSITION FOR CONTENT-BASED IMAGE RETRIEVAL

Pages

  115-125

Abstract

 In this paper, a novel low-level image FEATURE EXTRACTION and indexing scheme based on STRUCTURE-texture IMAGE DECOMPOSITION is presented. The main idea of this work is to decompose database images to STRUCTURE and TEXTURE sub-images to decrease the destructive effects of simultaneous existence of STRUCTURE and TEXTURE information in the image in indexing phase. It is also shown that precision in a typical CONTENT-BASED IMAGE RETRIEVAL system can considerably increase by combining the feature vectors extracted from STRUCTURE and TEXTURE sub-images. An image database containing 10000 images of 82 different semantic groups is used to evaluate the proposed method. The results confirm the effectiveness of this method.

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    Cite

    APA: Copy

    HAYATI, S., SARYAZDI, S., & NEZAMABADI POUR, H.. (2013). STRUCTURE-TEXTURE IMAGE DECOMPOSITION FOR CONTENT-BASED IMAGE RETRIEVAL. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, 10(2), 115-125. SID. https://sid.ir/paper/228436/en

    Vancouver: Copy

    HAYATI S., SARYAZDI S., NEZAMABADI POUR H.. STRUCTURE-TEXTURE IMAGE DECOMPOSITION FOR CONTENT-BASED IMAGE RETRIEVAL. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR[Internet]. 2013;10(2):115-125. Available from: https://sid.ir/paper/228436/en

    IEEE: Copy

    S. HAYATI, S. SARYAZDI, and H. NEZAMABADI POUR, “STRUCTURE-TEXTURE IMAGE DECOMPOSITION FOR CONTENT-BASED IMAGE RETRIEVAL,” NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, vol. 10, no. 2, pp. 115–125, 2013, [Online]. Available: https://sid.ir/paper/228436/en

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