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Image Retrieval Using Intensity Gradients and Texture Chromatic Pattern: Satellite Images Retrieval

Author

Listed:
  • I.Jeena Jacob

    (GITAM University, Bangalore, India)

  • Betty Paulraj

    (Kumaraguru College of Technology, India)

  • P. Ebby Darney

    (Department of Electrical and Electronics Engineering, SCAD College of Engineering and Technology, India)

  • Hoang Viet Long

    (People's Police University of Technology and Logistics, Vietnam)

  • Tran Manh Tuan

    (Thuyloi University, Vietnam)

  • Harold Robinson Yesudhas

    (School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India)

  • Vimal Shanmuganathan

    (Department of Information Technology, National Engineering College, Kovilpatti, India)

  • Golden Julie Eanoch

    (Department of Computer Science and Engineering, Anna University, Tirunelveli, India)

Abstract

Methods to retrieve images involve retrieving images from the database by using features of it. They are colour, shape, and texture. These features are used to find the similarity for the query image with that of images in the database. The images are sorted in the order with this similarity. The article uses intra- and inter-texture chrominance and its intensity. Here inter-chromatic texture feature is extracted by LOCTP (local oppugnant colored texture pattern). Local binary pattern (LBP) gives the intra-texture information. Histogram of oriented gradient (HoG) is used to get the shape information from the satellite images. The performance analysis is land-cover remote sensing database, NWPU-VHR-10 dataset, and satellite optical land cover database gives better results than the previous works.

Suggested Citation

  • I.Jeena Jacob & Betty Paulraj & P. Ebby Darney & Hoang Viet Long & Tran Manh Tuan & Harold Robinson Yesudhas & Vimal Shanmuganathan & Golden Julie Eanoch, 2021. "Image Retrieval Using Intensity Gradients and Texture Chromatic Pattern: Satellite Images Retrieval," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 17(1), pages 57-73, January.
    • Handle: RePEc:igg:jdwm00:v:17:y:2021:i:1:p:57-73
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