Narendra, V G and Amithkumar, G (2019) Intelligent system to estimate the morphological and surface color properties of almond’s varieties and classify using soft computing techniques. Journal of Advanced Research in Dynamical and Control Systems, 10 (13). pp. 2494-2500. ISSN 1943023X

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Abstract

Image processing techniques are increasingly applied in quality evaluation and sorting applications of agricultural and food products. This work has accessed the use of image processing for inspecting surface color as well as morphological properties of almonds varieties. A computer vision system (CVS) is developed and experiments are conducted to determine color change and geometric properties in almonds varieties. Conversion of RGB to HCL values is done via image processing and prediction models are developed to estimate geometric properties and color parameters from CVS data. Compared to the calculated color values hue angle and chroma, a yellowness index computed is found to be much more adept accurately predicting almonds varieties color from CVS data. Therefore, it is shown that the CVS was capable of producing accurate morphological and color values for the almonds varieties investigated. The findings of this study can be incorporated for development of a robust system for quality prediction and establishment of a CVS for automatic grading and sorting of almonds

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