Osama A. Alhashi; Fathey S. Almahjob; Abdelsalam A. Almarimi; Abdosllam M. Abobaker
The aim of this paper is to assess and determine the ripeness and quality of apples. To meet the goals, we propose and implement certain methodologies and algorithms that are based on digital fuzzy image processing, content predicated analysis, and statistical analysis. We found that the proposed algorithm is an efficient one as it is able to detect and sort the apples with more accuracy in grading compared to human expert sorting. The textures on apple skin are captured using digital camera. These images are filtered using image processing technique. All the information gathered is processed using MATLAB to determine the apple ripeness accuracy. In MATLAB, first we find the RGB component of a good apple and a ripen apple. Then, the image is converted to a grayscale image in order to obtain the histogram graph for analyzing the results. Besides, we also apply the same algorithm to orange fruit to verify the validity. The results presented in this paper corroborate that the automated grading system helps to minimize the processing time as well as the assessment error.