Application of Image Processing Techniques for Quality Control of Mushroom

Abstract

Background: Mushroom is one of the sources for protein supply, and it has taken into consideration among most countries in the world due to its rich medicinal features. Nowadays, due to the mechanization of traditional methods and quality control of products, it is possible to evaluate the quality of mushrooms with the help of image processing techniques. Methods: In this study, image processing systems were used to determine the appearance quality of mushrooms. Using the properties of color, area, weight, and volume obtained from data mining techniques, artificial neural networks and fuzzy logic system mushroom quality was evaluated. Results: A total of 250 images in three categories of defective, moderate were assessed. The correct detection rate by the image processing system was 95.6%. Conclusion: The results of this study showed the optimum performance of image processing systems for assessing the quality of mushrooms. The superiority of image processing systems compared to traditional method can be observed in the quality of increased efficiency and high accuracy, as well as the reduction of costs and destructive effects in the production and packaging of food products.

Keywords

• Image processing
• data mining
• Mushroom quality
• neural network
• fuzzy logic