Design and Research on Visual Recognition System for Spoiled Fruit Detection

Fruits are an essential part of a healthy diet, rich in vitamins, minerals, and dietary fiber. However, during storage, transportation, and marketing, fruits are prone to spoilage due to various factors such as microbial infection, physical damage, and improper storage conditions. Spoiled fruits not only lose their nutritional value and sensory quality but also pose potential health risks to consumers. Therefore, effective detection of spoiled fruits is crucial for ensuring food safety, reducing economic losses, and improving the efficiency of the fruit supply chain.Traditional methods for fruit quality inspection mainly rely on manual visual inspection, which is time - consuming, labor - intensive, and subjective. Moreover, it is difficult to detect early - stage spoilage accurately. With the rapid development of computer vision technology, visual recognition systems have shown great potential in fruit quality assessment. These systems can capture and analyze fruit images, extract relevant features, and classify fruits into different quality grades. The application of visual recognition systems in spoiled fruit detection can overcome the limitations of traditional methods and provide a more objective, efficient, and accurate solution.The objective of this study is to design and develop a visual recognition system for spoiled fruit detection. The main innovation of this research lies in the integration of multiple image processing techniques and advanced classification algorithms to improve the accuracy and reliability of spoiled fruit detection. By using a combination of color, texture, and shape features, the system can effectively distinguish between fresh and spoiled fruits, even in the early stages of spoilage.