FruitScan Pro : Fruit Disease and Quality Detection Application

FruitScan Pro : Fruit Disease and Quality Detection Application

Mr. S. H. Sangale1, Shiwani Nanaware2, Rituja Malode3, Shraddha More4, Madhura Patil5

*1 Professor, Department of Computer Technology, K.K. Wagh Polytechnic, Nashik, Maharashtra, India.

*2,3,4,5 Department of Computer Technology, K.K. Wagh Polytechnic, Nashik, Maharashtra, India.

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Abstract - This research paper proposes a revolutionary approach to agriculture by combining the latest image processing technologies with machine learning. The agricultural industry, which is vital for India’s economy, needs efficient methods for monitoring fruit health. Manual monitoring is time consuming and often inadequate. In this paper, we propose a smart farming approach using image processing techniques. This approach improves image quality, segmenting images, extracting features, and classifying diseases and their cures. Fruit diseases are a major economic challenge around the world. Therefore, it is necessary to identify them quickly. Our proposed system offers fast and automatic disease detection. Preprocessing, extracting features, classifying, training/testing. The results prove its effectiveness for accurate disease detection and solutions. As the demand for agricultural productivity increases, this method will be a valuable tool for increasing fruit production with minimum human intervention. Image processing for effective implementation.

Key Words: Fruit Disease, Solution, Image Preprocessing, Feature Extraction, Classification.