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Evaluating the effect of super-resolution for automatic plant disease detection: application to potato late blight detection

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Abstract

Precise and automatic plant disease detection represent a fundamental research topic. Indeed, traditional or manual disease detection can be laborious, inaccurate and time-consuming. In this work, a particular attention is given to automatic potato late blight disease detection. In fact, this devastating pathogen leads every year to a significant reduction in potato yields. In addition, since potatoes are a major food source for many nations, decreased production generate a real food insecurity. Therefore, considering these challenges, using advanced techniques in computer vision and machine learning allowed farmers to swiftly and accurately identify disease. The main objective of this research work is to generate a super-resolved labeled dataset (SRD) and evaluate its impact on plant disease detection. Three states of the art object detection methods (Faster-RCNN, Detr and Yolo V8) have been used to conduct an exhaustive evaluation on the effect of using a super-resolved dataset to perform detection. The obtained results show that the detection of potato late blight disease is enhanced using SRD. Training Yolo V8 model on SRD outperform other trained models in detecting very small lesions. In fact, training Yolo V8 on SRD reached higher mAP, lower Loss values and a reasonable inference time, making it suitable for real time applications.

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Data availability

The data that support the findings of this study are openly available in: https://www.kaggle.com/datasets/emmarex/plantdisease

Additional data related to this work can be obtained on request from the corresponding author.

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  1. Djillali Liabes University of Sidi Bel Abbes, BP89, Cité Larbi BenMhidi, 22000, Sidi Bel Abbes, Algeria

    Mazari Sarah, Meddoudi Abdlemadjid, Benameur Sarah, Hadjadj Yacine & Chikr El Mezouar Miloud

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Sarah, M., Abdlemadjid, M., Sarah, B. et al. Evaluating the effect of super-resolution for automatic plant disease detection: application to potato late blight detection. Multimed Tools Appl 83, 78469–78487 (2024). https://doi.org/10.1007/s11042-024-18574-5

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