Dhan-Shomadhan: A Dataset of Rice Leaf Disease Classification for Bangladeshi Local Rice

TL;DR

This paper introduces a comprehensive dataset of 1106 rice leaf images from Bangladesh, capturing five major diseases with varied backgrounds to aid in disease classification and detection using computer vision.

Contribution

The paper presents a new dataset specifically for Bangladeshi rice diseases, including diverse backgrounds to improve real-world applicability and accuracy in disease classification tasks.

Findings

Dataset covers five major rice diseases in Bangladesh.

Includes images with field and white backgrounds for versatile use.

Facilitates development of computer vision models for rice disease detection.

Abstract

This dataset represents almost all the harmful diseases for rice in Bangladesh. This dataset consists of 1106 image of five harmful diseases called Brown Spot, Leaf Scaled, Rice Blast, Rice Turngo, Steath Blight in two different background variation named field background picture and white background picture. Two different background variation helps the dataset to perform more accurately so that the user can use this data for field use as well as white background for decision making. The data is collected from rice field of Dhaka Division. This dataset can use for rice leaf diseases classification, diseases detection using Computer Vision and Pattern Recognition for different rice leaf disease.