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Combination of multiple classifiers for automatic recognition of diseases and damages on plant leaves

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Abstract

In this paper, we present an automatic recognition system of diseases and damages on plant leaves. The proposed system is based on classifiers combination technique, in which we have two variants of combination: serial combination of two classifiers, and hybrid combination of three classifiers including a serial combination of two classifiers in parallel with an individual classifier. Three types of features are adopted including color, texture and shape. The tests of this study to evaluate the three variants of combination are carried out on a database of 600 images of six classes (Leaf miners, Tuta absoluta and Thrips, Early blight, Late blight and powdery mildew). The comparison of results between the two methods serial and hybrid of the proposed system indicates that significant performances were obtained by applying the hybrid method for the recognition of diseases and damages on plant leaves.

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Authors and Affiliations

  1. IRF-SIC Laboratory, Ibn Zohr University, B.P. 80000, Agadir, Morocco

    Ismail El Massi, Youssef Es-saady, Mostafa El Yassa & Driss Mammass

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  1. Ismail El Massi
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  2. Youssef Es-saady
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  3. Mostafa El Yassa
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  4. Driss Mammass
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Correspondence to Ismail El Massi.

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El Massi, I., Es-saady, Y., El Yassa, M. et al. Combination of multiple classifiers for automatic recognition of diseases and damages on plant leaves. SIViP 15, 789–796 (2021). https://doi.org/10.1007/s11760-020-01797-y

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  • DOI: https://doi.org/10.1007/s11760-020-01797-y

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