ANN Based Colour Detection in Tea Fermentation

Colour and texture are important parameters in foods processing industries. Both these two factors represent meaningful visual stimuli and can be represented by a model for quality control of the products. Some food processing industries give emphasis on the coloury compounds towards quality of the food items. Intensive processing in complex controlled environments of tea fermentation requires supervision and control of the process as early as possible. The design and development of a PC based color matching system is attempted for the Tea industry. In this paper a comparison / matching technique for colour of test image with a standard data set is adopted. The neural network technique is considered for making the algorithm more trained and adaptable to detect the optimum colour of tea during fermentation. The result is compared with the decision made by tea tasters in the tea industry.