Research on Beef Skeletal Maturity Determination Based on Shape Description and Neural Network
Abstract: Physiological
maturity is an important indicator for beef quality. In traditional method, the
maturity grade is determined by subjectively evaluating the degree of cartilage
ossification at the tips of the dorsal spine of the thoracic vertebrae. This
paper uses the computer vision to replace the artificial method for extracting
object (cartilage and bone) regions. Hu invariant moments of object region were
calculated asthe regional shape characteristic parameters. A trained Hopfield
neural network model was used forrecognizing cartilage and bone area in
thoracic vertebrae image based on minimum Euclidean distance. The result showed
that the accuracy of network recognition for cartilage and bone region was
92.75% and 87.68%, respectively. For automatically maturity prediction, the
accuracy of prediction was 86%. Algorithmproposed in this paper proved the
image description and neural network modeling was an effective method for
extracting image feature regions.
Author: Xiangyan Meng, Yumiao
Ren, Haixian Pan
Journal Code: jptkomputergg150096
