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A Curated Dataset for Spinach Species Identification

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Computer Vision and Image Processing (CVIP 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1777))

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Abstract

India has a large population of spinach eaters. Despite this fact most people and young generation have difficulty in distinguishing the spinach species because of the structure similarity of many plant species. So, automated spinach recognition will support the people community to a greater extent. In this study, we present spinach dataset, a freely accessible annotated collection of images of spinach leaves in Indian scenario. We propose three different custom designed convolutional neural networks (CNN) and compare the performance of the same. Also we apply the transfer learning approach using MobileNetV2 pretrained model for this spinach species recognition. Using transfer learning approach we got an accuracy of 92.96%.

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Acknowledgement

This study is done as a part of Kaggleá¾½s Open Data Research Grant 2020.

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Authors and Affiliations

  1. Centre for Image Processing and Pattern Recognition, Mepco Schlenk Engineering College, Sivakasi, India

    R. Ahila Priyadharshini, S. Arivazhagan & M. Arun

Authors
  1. R. Ahila Priyadharshini
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  2. S. Arivazhagan
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  3. M. Arun
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Corresponding author

Correspondence to R. Ahila Priyadharshini .

Editor information

Editors and Affiliations

  1. Visvesvaraya National Institute of Technology Nagpur, Nagpur, India

    Deep Gupta

  2. Visvesvaraya National Institute of Technology Nagpur, Nagpur, India

    Kishor Bhurchandi

  3. Indian Institute of Technology Ropar, Rupnagar, India

    Subrahmanyam Murala

  4. Indian Institute of Technology Roorkee, Roorkee, India

    Balasubramanian Raman

  5. Indian Institute of Technology Roorkee, Roorkee, India

    Sanjeev Kumar

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Ahila Priyadharshini, R., Arivazhagan, S., Arun, M. (2023). A Curated Dataset for Spinach Species Identification. In: Gupta, D., Bhurchandi, K., Murala, S., Raman, B., Kumar, S. (eds) Computer Vision and Image Processing. CVIP 2022. Communications in Computer and Information Science, vol 1777. Springer, Cham. https://doi.org/10.1007/978-3-031-31417-9_17

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  • DOI: https://doi.org/10.1007/978-3-031-31417-9_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-31416-2

  • Online ISBN: 978-3-031-31417-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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