猪眼肌B超图像纹理特征提取与分类  

Texture Feature Extraction and Classification of Pork Loin Ultrasonography Images

作　　者：张建勋[1] 李涛[1] 孙权[1] 谢婷婷[1] 

机构地区：[1]重庆理工大学计算机科学与工程学院,重庆400054

出　　处：《重庆理工大学学报（自然科学）》2013年第2期74-78,共5页Journal of Chongqing University of Technology：Natural Science

基　　金：重庆理工大学研究生创新基金资助项目

摘　　要：提出了猪眼肌B超图像的纹理特征提取与分类方法,可以应用于猪眼肌肌内脂肪含量的计算机辅助检测判断。对猪眼肌B超图像特征区域采用基于纹理共生矩阵的算法提取了5种纹理特征量。使用相关性分析的方法对提取的5种特征量进行筛选,最后确定3种主要特征量反映猪眼肌B超图像纹理特征,并使用BP神经网络实现分类。对135组已测数据随机选取训练集合测试集。多次随机试验表明,所提取的算法达到了较高的分类准确率,为生猪肉质无损检测研究提供了有价值的参考。The method of texture feature extraction and classification of pork loin B ultrasound image is proposed, which can be applied to the computeraided judgment the intramuscular fat content of pork loin. 5 texture features which are based on the texture of the co-occurrence matrix are extracted from the B ultrasound image of pork loin according to the digital image processing algorithm. Using the correlation analysis method to select the key texture extraction in the first step. Then, the classification is realized based on the BP neural network. The train set and test set are randomly chosen from 135 cases. Tests performed show that the proposed method result in a high classification accuracy, which will provide the researcher a valuable opinion on the pork fat content detection.

关 键 词：猪眼肌 B超图像 纹理特征 BP神经网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]