CURRENT IMPLEMENTATION REPORT

Automatic Wheat Disease Detection Using Image Processing and Convolutional Neural Network for Farmers

AI-powered early detection for healthier crops, better productivity, and timely farmer decisions.

AI Powered CNN Model Smart Farming
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About Project

1. Introduction

Agriculture plays a significant role in India’s economy, and wheat is one of the major staple crops cultivated by farmers. Early detection of wheat diseases is essential to prevent yield loss and ensure food security. Manual disease detection is time-consuming and may lead to inaccurate results.

This project aims to develop an Automatic Wheat Disease Detection System using Image Processing and Convolutional Neural Network (CNN). The system helps farmers identify wheat leaf diseases at an early stage by analyzing leaf images and providing accurate predictions.

The system supports farmers in taking timely preventive measures, improving crop health and productivity.

Objectives

2. Project Objective

  • To develop an image-based disease detection system for wheat crops.
  • To apply image preprocessing techniques for better feature extraction.
  • To build a Convolutional Neural Network (CNN) model for disease classification.
  • To provide farmers with accurate and quick disease prediction results.
  • To develop a simple and user-friendly interface.

Model Training Progress

Model Training: In Progress

68%

TensorFlow / Keras based CNN training is currently in progress.

Dataset Preparation

3. Dataset Preparation (Completed)

The dataset consists of wheat leaf images categorized into healthy and diseased classes.

Input Data Used

  • Wheat leaf images
  • Diseased leaf images
  • Healthy leaf images

Output Label

  • Disease Type (e.g., Rust, Smut, Blight, Healthy)

Dataset Status

  • Collected and verified
  • Cleaned and labeled properly
  • Resized for CNN model training
  • Augmented to improve model performance

Technology Stack

4. Machine Learning Algorithm Used

Convolutional Neural Network (CNN)

The system uses a Convolutional Neural Network, which is a deep learning algorithm mainly used for image classification tasks.

Why CNN?

  • High accuracy in image classification
  • Automatically extracts important features
  • Reduces manual feature engineering
  • Suitable for agricultural disease detection
  • Works effectively with large image datasets

CNN applies convolution, pooling, and fully connected layers to classify wheat leaf images accurately.

6. Technology Stack

Frontend

HTML

CSS

JavaScript

Backend

Python

TensorFlow / Keras

OpenCV

(Currently model training is in progress)

System Workflow

5. System Architecture (Current Working Model)

User uploads wheat leaf image
Frontend sends image to backend
Image preprocessing is performed
Trained CNN model analyzes image
Prediction shown on dashboard

Modules Completed

7. Modules Completed

  • Dataset Collection and Preparation
  • Image Preprocessing Module
  • CNN Model Design
  • Dashboard Page (Frontend UI completed)
  • Model Training (In Progress)

Current Status

8. Current Implementation Status

  • Dataset successfully collected and labeled.
  • Image preprocessing pipeline completed.
  • CNN architecture designed and configured.
  • Frontend dashboard page completed.
  • Backend integration partially completed.
  • Model training process is currently ongoing.

Expected Outcome

9. Expected Outcome

Once model training is completed:

  • The system will accurately detect wheat diseases from images.
  • Farmers can upload leaf images easily.
  • The system will provide real-time disease prediction.
  • Early detection helps reduce crop loss.
  • Expected model accuracy: High (based on CNN performance in image classification tasks).

Future Enhancements

10. Future Enhancements

  • Add disease severity detection.
  • Provide treatment suggestions for detected disease.
  • Deploy system using cloud platform.
  • Integrate mobile application for easy farmer access.
  • Add multi-language support.

Upload Wheat Leaf Image (Demo)

Demo Feature

Select a wheat leaf image to preview and get a dummy prediction result.

Wheat leaf preview will appear here

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Prediction Result

Status

Waiting for image upload...

Team INTELLICORE

Team Name: INTELLICORE Team No: 8

Vaishnavi R

611724243056

Prathiksha J

611724243031

Taj S

611724243052

Thirubuvaneswari S

611724243054