Computer Vision and Video Analytics System for Plant Growth and Disease Detection


Infocomm - Big Data, Data Analytics, Data Mining & Data Visualisation
Infocomm - Video/Image Processing
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Crop production is one of the major sources of income in the world and more than half of our population depends on agriculture for livelihood. Crop cultivation is a tedious and laborious process. Crops infected with disease would be devastating to the farmer. One of the major concerns is the lack of knowledge and manpower to identify disease crops at an early stage to prevent the spread of infection to healthy crops.

This Technology Offer is a fast and accurate, artificial intelligence (AI)-based computer vision system that can detect plant disease. This system is more reliable and scalable than the traditional, manual methods in detecting plant disease. It uses video analytics, which has an advantage that the algorithms automatically analyse large collections of images and identify features that can be used to categorize images with minimum error. Images of plant leaves are digitally pre-processed to get clear, noiseless enhanced leaf images. These enhanced images are then used for analysis to detect diseases. Generally, plant leaf image color and texture are unique features, which can be used to detect and analyse the diseases.


The traditional method of checking for diseases in plants is through visual checks, but this method is not consistent, and is inefficient in detecting the diseases associated with plants. A faster and scalable alternative method is the use of computer vision which can be more reliable and productive. This Technology Offer uses computer vision and video analytics to evaluate the probability of each disease for plants of any color. There are many variations of the same disease among each class of crops; every disease presents specific characteristics that make them different from others, e.g., colour, texture, shape. These characteristics and their various combinations are used by the algorithm to determine the specific disease present. 


The trained model detects diseased plants within acceptable confidence.  The research and development efforts have the potential to be translated into IP in the following areas:

  • Once co-related with real-time data, it can be a predictive tool to enable farmers to “predict” with a known accuracy the probability of the plant disease.
  • Farmers will also be able to formulate suitable interventions be it medications or other means. A detailed study with control groups will be useful to determine the effectiveness of said interventions.
  • Further developments with appropriate refinements to the type, suitability, sensitivities, precision and accuracy of the detector may enable early detection of other diseases.
  • The device will also be useful as an early warning detector for plant disease infections.


Customer benefits include:

  • Early intervention to prevent the spread of disease, and hence improve overall yield.
  • Reduce manpower and labour required to do visual checks.

Currently, proof-of-concept stage is completed, and this Technology Offer is available for project collaborators or consultancy projects to field-test the technology.


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