classification tool for agri seed varieties
In this research work, we intends to develop an Agri-App for rice seed classification using Artificial Neural Network (ANN). It have multiple steps including images acquisition of rice, then applying pre-processing techniques like thresholding, Canny edge detection, f
Project Title
classification tool for agri seed varieties
Project Area of Specialization
Project Summary
In this research work, we intends to develop an Agri-App for rice seed classification using Artificial Neural Network (ANN). It have multiple steps including images acquisition of rice, then applying pre-processing techniques like thresholding, Canny edge detection, feature extraction, morphological features extracted from the image are forwarded to Neural Network. This effort will help to categorize the appropriate quality rice sample based on its parameters. The performance of image processing condensed the time of action and enhanced the crop identification significantly.
Project Objectives
- To develop an Agri-App for rice classification using Artificial Neural Network (ANN).
- to provide a substitute solution for quality analysis of rice.
- to lessen the required time and cost
- to remove the human error.
Project Implementation Method
- First the image acquisition of rice is done
- Then image segmentation is done by using the Canny edge detection technique
- After that diff morpholoical features are extracted
- Artificial Neural Network is applied on the extracted data and the results are obtained
- By using the obtained results and Android Application will be made so that the quality of rice can easily be estimated
Benefits of the Project
1.To provide a substitute solution for quality analysis which lessen the required time and cost.
2.To identify and evaluate demand-driven options for improved nutrition and equity and ecosystem stability.
Technical Details of Final Deliverable
Mobile App for farmers.
Final Deliverable of the Project
Type of Industry
Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Android Mobile with high performance | Equipment | 1 | 35000 | 35000 |
| Total in (Rs) | 35000 |
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