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Improved Similar Images Retrieval: Dynamic Multi-feature of Fusion a Method with Texture Features

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Advances in Electrical and Computer Technologies (ICAECT 2020)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 711))

Abstract

Rapid advances in digital image technology contributes huge amount of images in the many fields like digital libraries, medical imaging, Web image searching, etc. This chapter attempts to present novel approach in CBIR, which is based on the combined texture features. This approach mainly aims at designing the effectiveness of the image retrieval system. Thus, in this chapter, multiple features method has been proposed in order to create a novel hybrid features by 4Dir-GLCMEDGE method. This method majorly has three process flows, (a) a process to find the four diagonal texture features (b) a process to find the local binary pattern (LBP) features (c) It is a fusion of diagonal texture features and edge features. This fusion aims at combining and reducing multiple image features into single image feature. Selecting a query image as input, more similar images can be retrieved with the help of the proposed hybrid features. Using the hybrid features, based on two distance metrics such as euclidean and manhattan metics, results in more similar imges. This proposed method has been tested with Corel and Wang datasets. The test results, compared to the previous methods, are encouraging and found to be better than existing methods. The image retrieval result improvements in the new approach method over existing methods have been proved by in terms of precision and recall.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Pondicherry University, Kalapet, Puducherry, 605014, India

    P. John Bosco

  2. Department of Banking Technology, Pondicherry University, Kalapet, Puducherrry, 605014, India

    S. Janakiraman

Authors
  1. P. John Bosco
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  2. S. Janakiraman
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Corresponding author

Correspondence to P. John Bosco .

Editor information

Editors and Affiliations

  1. Department of Electrical and Electronics Engineering, SVS College of Engineering, Coimbatore, Tamil Nadu, India

    Thangaprakash Sengodan

  2. Department of Electronic and Communication Engineering, Kuwait College of Science and Technology, Doha, Kuwait

    M. Murugappan

  3. Department of Computer and Information Sciences, Covenant University, Ota, Nigeria

    Sanjay Misra

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John Bosco, P., Janakiraman, S. (2021). Improved Similar Images Retrieval: Dynamic Multi-feature of Fusion a Method with Texture Features. In: Sengodan, T., Murugappan, M., Misra, S. (eds) Advances in Electrical and Computer Technologies. ICAECT 2020. Lecture Notes in Electrical Engineering, vol 711. Springer, Singapore. https://doi.org/10.1007/978-981-15-9019-1_10

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  • DOI: https://doi.org/10.1007/978-981-15-9019-1_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-9018-4

  • Online ISBN: 978-981-15-9019-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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