Enhanced Field-Based Detection of Potato Blight in Complex Backgrounds Using Deep Learning.

Plant Phenomics : a Science Partner Journal
Joe JohnsonVijay Kumar Dua

Abstract

Rapid and automated identification of blight disease in potato will help farmers to apply timely remedies to protect their produce. Manual detection of blight disease can be cumbersome and may require trained experts. To overcome these issues, we present an automated system using the Mask Region-based convolutional neural network (Mask R-CNN) architecture, with residual network as the backbone network for detecting blight disease patches on potato leaves in field conditions. The approach uses transfer learning, which can generate good results even with small datasets. The model was trained on a dataset of 1423 images of potato leaves obtained from fields in different geographical locations and at different times of the day. The images were manually annotated to create over 6200 labeled patches covering diseased and healthy portions of the leaf. The Mask R-CNN model was able to correctly differentiate between the diseased patch on the potato leaf and the similar-looking background soil patches, which can confound the outcome of binary classification. To improve the detection performance, the original RGB dataset was then converted to HSL, HSV, LAB, XYZ, and YCrCb color spaces. A separate model was created for each color space an...Continue Reading

References

Jun 27, 2008·IEEE Transactions on Pattern Analysis and Machine Intelligence·Efstathios HadjidemetriouShree K Nayar
Sep 26, 2014·TheScientificWorldJournal·Dina KhattabMohamed Fahmy Tolba
Mar 29, 2016·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Thomas A LampertPierre Gancarski
Jun 14, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence·Shaoqing RenJian Sun
Oct 8, 2016·Frontiers in Plant Science·Sharada P MohantyMarcel Salathé

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Software Mentioned

Mask
GPU
CentOS
Keras
Mask R - CNN
VGG Image Annotator ( VIA )
SSD
YOLO
Python
TensorFlow

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