Fuzzy C-means measurement of mass base on image features

Abstract

Mass of an object is an important characteristic for quality assessment. However, in some cases, it is hard to measure the mass of objects with instruments directly. In this paper, we proposed a novel method based on Fuzzy c-means (FCM) to measure the mass of an object by analyzing the deformation degree in a grid pattern. In the spatial field, thin plate spline (TPS) algorithm was adopted to calculate the minimum deformation bending energy in order to give a quantitative analysis of the weight; In frequency domain, the Fast Fourier Transform (FFT) algorithm was used to calculate the spectrum within a deformation frequency area before and after the change of grids, from which the relationship between weight and spectrum was investigated using FCM algorithm. Two different equations evaluated by the above two methods were proposed in order to calculate the mass of an object. Both of them showed a high level of explanatory power of R2 (R2 = 0.9833 and R2 = 0.9698, respectively). The equations were then used to determine the estimated mass. Estimated and measured values were plotted against each other. A high correlation (R2 = 0.9833 and R2 = 0.9698, respectively) was found between actual and calculated mass. Finally, Bland-Altman plot was introduced to access the agreement of the calculated mass and the actual mass. The average bias was –54.408 g and –0.007 g for spatial domain method and frequency domain method, respectively. Theoretical analysis and experiments were performed to verify the effectiveness of our approaches.