|Authors: ||C.C. Teoh, A.R.M. Syaifudin|
|Keywords: ||computer vision system, segmentation, thresholding, estimate weight, fruit|
Mango is one of the popular fruits produced in Malaysia and can be graded into different groups according to their size, maturity, disease and defects.
Size is one major parameter that consumer identifies with the quality of fruits.
Manually grading size of mango is laborious, tedious and costly.
An automatic grading system like a computer vision system can be used to improve the quality of grading and reduce dependency on available manpower.
Image analysis is the core of the computer vision system to achieve the required measurement and grading of fruits.
The objective of this study is to develop an algorithm for grading size of mango based on the image analysis process.
Size of mango can be estimated in different ways using image analysis.
One method is to plot the area of mango measured by image analysis against the actual weight of mango in a graph.
If correlation between the two measurements is high then it is possible to create a formula from the graph for estimating the size or weight of mango.
In this study, the results show that the area measured by image analysis has high correlation with the actual weight of mango with R2 = 0.934. The results of grading size of mango using a formula created in the experiment are also satisfying and encouraging.
Download Adobe Acrobat Reader (free software to read PDF files)
URL www.actahort.org Hosted by KU Leuven