The geometric parameters along with related colour properties of food and agricultural products are important in order to characterize and describe its quality. The application of image processing technique for this purpose can certainly reduce the human drudgery while guaranteeing the quality of produce. In this paper, a new geometric and colour quality parameters estimation methods suggested, to provide automatic and intuitive way of quality inspection of Cashews kernels from an image accurately. The geometric parameters are obtained manually and from proposed algorithm. We have investigated the hardware-oriented, human-oriented, and instrumental colour spaces for measurement of colour parameters of Cashews kernels. It is estimated from our research that the statistical measurements of each Cashews kernel grades, from the proposed methods. Finally the paper concludes by highlighting the necessity of such computer vision system and insight into the methodology that attempts to fix the universal estimation of statistical measurements of geometric and colour parameters of Cashews kernels grade.
Article Review Status: Review Completed - Accepted (Pay Publication Fee)
If your article’s review has been completed, please ensure you check your email for feedback.
This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License