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Image retrieval technique using the clustering based on rearranged radon transform

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Abstract

This study proposed a new image retrieval technique in which the existing radon transform that was used for image retrieval is reinforced with noise invariance. For this, a radon transform was performed on an inquiry image which had been preprocessed to extract vector values and then the vector values were arranged depending on size to extract a second feature vector. After clustering and normalizing the levels of vector values based on the second feature vector, the feature vector was created. For a simulation on the image retrieval technique using the clustering based on rearranged radon transform, diverse images were used in this experiment. For performance analysis, the system proposed was compared with the retrieval system using a rearrangement hough transform based on voting number. As a result, the proposed image retrieval technique was more robust to geometric transforms such as rotated and scaled in the retrieval technique using the general radon transform and standard hough transform, and it had recall enhanced to 0.05 and precision enhanced to 0.04 in comparison with the rearrangement hough transform based on voting number.

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Acknowledgments

This study was supported by research funds from Chosun University, 2014.

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Authors and Affiliations

  1. The College of General Education, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju, South Korea

    Youngeun An

  2. A-joo Communications, Inc. Research Institute, 219 Pungseojwa-ro, Seo-gu, Gwangju, South Korea

    Jimin Lee

  3. The College of Electronic and Information Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju, South Korea

    Jongan Park

Authors
  1. Youngeun An
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  2. Jimin Lee
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  3. Jongan Park
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Correspondence to Jongan Park.

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An, Y., Lee, J. & Park, J. Image retrieval technique using the clustering based on rearranged radon transform. Multimed Tools Appl 75, 12983–12997 (2016). https://doi.org/10.1007/s11042-016-3527-7

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  • DOI: https://doi.org/10.1007/s11042-016-3527-7

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