Applying Linear Regression to Estimate Weight of Non Axi-Symmetric fruit - Fitriyah, Hurriyatul; Setiawan, Eko; Masruri, Muhammad Rifqi Radifan (Journal of Information Technology and Computer Science, 2020)
Weight is an important parameter in fruits’ quality identification. Measuring fruits’ weight using scale is tedious since fruits must be taken from tree and placed on contact to scale. Many researches have proposed non-contact estimation methods of fruits’ weight using 2D images. The studies were commonly applied in axi-symmetric fruits, such oranges. In this paper, an algorithm to estimate weight of non axi-symmetric fruit is developed. It used a Linear Regression rather than geometric-based methods as proposed by other researches. The non axi-symmetric fruits chosen was star fruits. It is a challenging fruits since its basic shape is not round but irregular star shape. The estimation used pixel count from one-view image of the fruits’ projection as feature. The proposed method has RMSE of 16.322 Gram and MAPE of 7.089% compare to the expected weights. It also has high Coefficient of Determination, R^2, 0.8829 compare to the weight scale measurement.