Estimating the surface area and volume of ellipsoidal ham using computer vision

An automatic method for estimating the surface area and volume of ham was developed using a sequence of image processing algorithm. To extract the shape of ham, three steps of image processing algorithm were firstly developed, i.e. image segmentation, noise reduction, and edge detection. Then the protrusion of ham formed by elastic netting was deleted with four steps, namely obtaining radii, wavelet transform, locating protrusion, and spline interpolation. Finally, based on the new shape of ham, the surface area and volume were estimated by two methods, i.e. the derived method and the partitioned method. The former was based on the three principal dimensions, i.e. length (L), width (W), and thickness (T), and the surface area and volume were derived mathematically, while the latter firstly divided ham into a number of sections and then summed the surface area and volume of each section to obtain the entire ones. The results obtained have demonstrated that the approaches proposed have the ability to estimate the surface area and volume of ham.