Monitoring and grading of tea by computer vision – A review

Tea being a high value crop throughout the world, its quality plays a significant role in its marketability. Currently, organoleptic methods such as inspection by human sensory panel, and instrument based approaches such as gas chromatography and colorimetric method have been reported as the quality monitoring tools in various stages of tea processing. These methods are time consuming, laborious, expensive and sometimes inaccurate. Therefore, to overcome the inaccuracy and inconsistency, computer vision techniques can be explored as an alternative to conventional techniques. This paper presents an overview of various computer vision based algorithms for colour and texture analysis with a special orientation towards monitoring and grading of made tea. Computer vision and image analysis are non-destructive procedures for sorting tea on the basis of its physical parameters viz. granule colour, shape, size and texture. Although diverse methods for estimation of above parameters were developed by researchers independently, all these can be related to each other.