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Related Experiment Video

Updated: Oct 29, 2025

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement
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Disease recognition in philodendron leaf using image processing technique.

Viswanath Muthukrishnan1, Seetharaman Ramasamy2, Nedumaran Damodaran1

  • 1CISL, University of Madras, Chennai, 600025, India.

Environmental Science and Pollution Research International
|July 10, 2021
PubMed
Summary

This study introduces a new method for plant disease recognition using hue, saturation, and value on grayscale Philodendron leaf images. The technique effectively identifies specks, enhancing disease detection capabilities.

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Area of Science:

  • Plant pathology
  • Image processing
  • Computer vision

Background:

  • Plant diseases significantly impact agriculture and require accurate detection methods.
  • Existing disease recognition techniques vary in complexity and effectiveness.
  • Philodendron leaf diseases, specifically specks, necessitate targeted identification strategies.

Purpose of the Study:

  • To develop an efficient image processing technique for recognizing diseases in Philodendron leaves.
  • To adapt color space models (hue, saturation, value) for grayscale image analysis in plant pathology.
  • To enhance the visibility and identification of disease-related specks on plant leaves.

Main Methods:

  • Conversion of natural color Philodendron leaf images to grayscale.
Keywords:
GrayscaleHueIntensitySegmentationSpherical coordinate system

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  • Application of hue, saturation, and value (HSV) color space techniques to grayscale images.
  • Image iteration and resizing to improve the simultaneous recognition of diseased areas.

    • Main Results:

    • The HSV technique applied to grayscale images successfully identified specks on Philodendron leaves.
    • Disease spots were highlighted on a brighter scale, improving their visibility.
    • The method demonstrated potential for accurate disease part recognition.

    Conclusions:

    • The proposed method offers a novel approach to plant disease recognition using adapted image processing techniques.
    • Converting to grayscale and applying HSV analysis is effective for identifying specific leaf pathologies like specks.
    • This technique can aid in early and accurate diagnosis of plant diseases.