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Optimum Selection of Image Object Attributes for Object-Based Image Analysis and High Classification Accuracy | SpringerLink
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Optimum Selection of Image Object Attributes for Object-Based Image Analysis and High Classification Accuracy

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Computer Vision and Image Processing (CVIP 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2010))

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Abstract

Object-based image analysis (OBIA) is extensively used for the classification of High-Resolution Satellite Imagery (HRSI). The various attributes of the image segments like spectral, spatial and textural, can be generated for analysis and classification purposes. However, the use of all these attributes may not lead to attaining high classification accuracy. Experiments have shown that, a suitable set of these features need to be identified for faster and accurate classification of imageries. The filter based methods like Chi-Square, Information-gain and ReliefF are extensively used for identification and ranking the best set of parameters. The random tree based Boruta machine learning feature ranking method is also used in identifying the feature ranking along with the above algorithms. Subsequently, a learner is fused with a filter and the resultant receiver operating characteristic (ROC) plot of the model has been used to identify the best accuracy and the minimal set of attributes for identifying an individual feature like roads, trees, grass, buildings and shadow. The best set of parameters for a class is identified by the best ROC plot. The best parameters are identified from Boruta feature analysis. The results indicate that the identified smaller feature set helps in enhancing classification accuracy.

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Authors and Affiliations

  1. IIT Roorkee, Roorkee, 247667, India

    Ganesh Khadanga & Kamal Jain

Authors
  1. Ganesh Khadanga
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  2. Kamal Jain
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Corresponding author

Correspondence to Ganesh Khadanga .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology, Jammu, India

    Harkeerat Kaur

  2. Indian Institute of Technology, Jammu, India

    Vinit Jakhetiya

  3. Indian Institute of Technology, Ropar, India

    Puneet Goyal

  4. Indian Institute of Information Technology, Jabalpur, India

    Pritee Khanna

  5. Indian Institute of Technology, Roorkee, Uttarakhand, India

    Balasubramanian Raman

  6. Indian Institute of Technology, Roorkee, Uttarakhand, India

    Sanjeev Kumar

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Khadanga, G., Jain, K. (2024). Optimum Selection of Image Object Attributes for Object-Based Image Analysis and High Classification Accuracy. In: Kaur, H., Jakhetiya, V., Goyal, P., Khanna, P., Raman, B., Kumar, S. (eds) Computer Vision and Image Processing. CVIP 2023. Communications in Computer and Information Science, vol 2010. Springer, Cham. https://doi.org/10.1007/978-3-031-58174-8_21

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  • DOI: https://doi.org/10.1007/978-3-031-58174-8_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-58173-1

  • Online ISBN: 978-3-031-58174-8

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