In this paper, an image processing technique for estimating the volume and mass of four citrus fruits was presented and discussed.
The method is quite general and may be readily applied for volume and mass computation of other axi-symmetric agricultural products such as carrot, cucumber, onion, melon, kiwifruit, pomegranate, and pear.
Based on the results presented in this paper, we can argue the proposed method is rotationally invariant and does not require fruit alignment on the conveyor.
The present work may be extended in several ways. For example, the surface area of the citrus fruits can also be computed in a similar way (Khojastehnazhand et al., 009).
The background segmentation method adapted here is not based on threshold values, and can readily be adapted for other fruits.
The method developed in this study provides an alternative to the traditional methods for measurement of volume, surface area, and mass of axi-symmetric agricultural products.
The estimated volume, surface area, and mass of fruits, and the already available RGB color information may be used for online sorting of various citrus fruits.
However, RGB system adapted in this paper could be sensitive to lighting or other conditions. Therefore, we have used HSI color space instead to develop a sorting device for grading citrus (Khojastehnazhand et al., 2008).
In the HSI system, hue value is comparatively stable and the color of citrus can be determined by calculating the average Hue value for the fruit. Works in this direction
is still in progress.