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Scene Classification Based on Local Binary Pattern and Improved Bag of Visual Words

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Advances in Computational Intelligence (IWANN 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9094))

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Abstract

Today, image classification is considered as one of the most important and challenging tasks in computer vision. This paper presents a new method for image classification using Bag Of Visual Words and Local Binary Patterns (LBP). The bag-of-visual-words (BoVW) model has been proven to be very efficient for image classification and image retrieval. However, most proposals directly use local features extracted from an image while ignoring hidden information that could be extracted from an image. To solve this problem, we propose a novel image classification method using information extracted from different channels of the image and the grayscale version of the image. In this way more discriminant information is extracted from the image and as a result the constructed BoVW model gives highly discriminative features that considerably increases the classification performance. In this work we embed features extracted using LBP into BoVW model to construct our proposed scene classification model. The choice of LBP as image feature descriptor is because of the fact that the content of most of the scene images contains textural information so extracting LBP features is a very wise choice compared to other popular image features like Scale Invariant Feature Transform (SIFT) that fails to capture image information in homogeneous areas or textual images. Experiments on Oliva and Torralba (OT) dataset demonstrate the effectiveness of the proposed method.

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Author information

Authors and Affiliations

  1. Department of Information Technology Engineering, School of Engineering, Tarbiat Modares University, Tehran, Iran

    Gholam Ali Montazer

  2. Department of Information Technology, Iranian Research Institute for Information Science and Technology (Iran Doc), Tehran, Iran

    Davar Giveki

  3. Department of Computer Science, University of Tehran, Tehran, Iran

    Mohammad Ali Soltanshahi

Authors
  1. Gholam Ali Montazer
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  2. Davar Giveki
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  3. Mohammad Ali Soltanshahi
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Corresponding author

Correspondence to Gholam Ali Montazer .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Malaga, Malaga, Spain

    Gonzalo Joya

  3. Polytechnic University of Catalonia, Vilanova i la Geltrú, Spain

    Andreu Catala

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© 2015 Springer International Publishing Switzerland

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Montazer, G.A., Giveki, D., Soltanshahi, M.A. (2015). Scene Classification Based on Local Binary Pattern and Improved Bag of Visual Words. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2015. Lecture Notes in Computer Science(), vol 9094. Springer, Cham. https://doi.org/10.1007/978-3-319-19258-1_21

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  • DOI: https://doi.org/10.1007/978-3-319-19258-1_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19257-4

  • Online ISBN: 978-3-319-19258-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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