摘要
在HSV颜色空间H分量图像上进行分割预处理,结合改进分水岭算法对牛眼肌与大理石花纹区域进行精确分割,对中国、日本及美国的大理石纹的标准等级图的特征参数作相关性分析,优选出5个表征大理石纹分布的特征参数,提出一种基于图像处理及Hopfield神经网络的自动评级方法,结果表明,对大理石花纹分级准确率达到87.23%。
Beef images were pretreated based on the hue component of the HSV color space, and an improved watershed algorithm was proposed to separate the rib-eye and beef marbling region from the images. Meanwhile, the correlations of characteristics parameters from U.S., Chinese and Japanese standard grading graphs were analyzed. Five characteristic parameters were selected for beef marbling distribution. A new automatic grading method based on improved watershed method and Hopfield network was proposed, and the results indicated that the accuracy of this method was 87.23%.
出处
《食品科学》
EI
CAS
CSCD
北大核心
2013年第1期140-145,共6页
Food Science
