Welcome

For the past 100 years, the tea process is largely controlled by hand-made interventions and the color of the tea leaves (both finished and mid-process) play a key role in the process efficiency, quality measurement and dissolving classification. tea. The development of digital image processing techniques has been successfully used to assess tea quality . Key components of the research include image segmentation, feature extraction, and classification. Image segmentation techniques are employed to separate individual tea leaves from the background, providing a basis for subsequent analysis. Feature extraction involves quantifying visual attributes, such as color intensity, texture patterns, and leaf morphology. The significance of this research lies in its potential to revolutionize the traditional methods of tea quality assessment, offering a more objective, efficient, and automated approach. The developed image processing techniques not only provide a reliable means of determining tea quality but also pave the way for real-time quality monitoring in tea production processes. This research contributes to the broader field of food quality assessment and sets a precedent for the application of image processing in the context of agricultural products