Estimation of the marbled score in live beef cattle based on ICA and US texture information

点击翻译按钮获取中文摘要

To accurately estimate the Beef Marbling Standard(BMS) number of live cattle using ultrasound echo imagings, we have developed a image recognition method by use of a neural network. We examine the efficiency of applying Independent Component Analysis(ICA) to the compression of multidimensional image features. We have implemented the estimation tests by use of ultrasound echo imagings measured from live cattles. The estimation accuracy was evaluated based on the cross validation method. The results confirmed that the correlation coefficient between the actual and the estimated values was higher by ICA (R=0.70, p<0.01) than by PCA (R=0.62, p<0.01). Also, we conducted the comparison experiments between the ICA based estimation and the estimation by an experienced inspector. The both methods examined the same ultrasound images. As a result, we confirmed that the proposed method had much the same capability as the experienced inspector to estimate BMS number.