基于颜色分形的水果计算机视觉分级技术

通过对不同着色等级的水果分析,以各色度在水果表面分布的分形维数为特征进行分级,该特征值不仅考虑了各色度点的累计特性,而且考虑了色度点空间分布特性,使颜色分级更符合实际情况。将各色度域分形维数作为模式处理,建立了人工神经网络识别模型。学习后的模型分级正确率高,达到95%,能够满足计算机视觉实时分级水果生产线的要求

Computer Vision Classification of Fruit Based on Fractal Color

By analysis of different hues of fruit, and according to fractal dimension of chroma distribution on superficies of fruit, the classification of fruits was carried out. The eigenvalues including both the accumulative characteristics and space distribution characteristics of various hue points make the hue classification corresponding to the practical situation. The identifying model of artificial neuron network was built when the fractal dimension in every hue area was considered as pattern and then was processed. After studying, the accuracy of classification reached 95%, which can meet the requirement of real time production line for the classification of fruits by computer vision.