基于鸡头特征的病鸡识别方法研究  

Recognition Method of Sick Yellow Feather Chicken Based on Head Features

作　　者：毕敏娜[1] 张铁民[1,2] 庄晓霖 焦培荣 

机构地区：[1]华南农业大学工程学院,广州510642 [2]国家生猪种业工程技术研究中心,广州510642 [3]华南农业大学兽医学院,广州510642

出　　处：《农业机械学报》2018年第1期51-57,共7页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金项目(51177053);广东省省级科技计划项目(2014A050503061)

摘　　要：健康黄羽鸡鸡冠鲜红、纹理均匀,鸡眼圆润有神,病鸡鸡冠萎缩变色、鸡眼半闭或全闭。本文提出了一种基于鸡冠及鸡眼构成的鸡头特征信息的病鸡识别方法。首先通过R、G、B分量色差信息去除背景,分析鸡身和鸡冠样本区域H分量分布特点,提取H分量分割阈值分割黄羽鸡。再利用H分量进行阈值分割得到黄羽鸡和鸡冠鸡垂。提出一种利用鸡冠和鸡垂轮廓上两点距离小于阈值的鸡头合并算法,再通过修正算法识别鸡头。在鸡头中,分别提取鸡眼瞳孔轮廓并获取形状几何特征,提取鸡冠的H分量共生矩阵特征,构成基于鸡头特征,采用ARA特征选择算法获得病鸡特征向量,采用支持向量机(SVM)分类器进行训练分类。实验结果表明,病鸡识别正确率为92.5%,表明利用机器视觉获取鸡头特征进行病鸡识别具有可行性和研究价值。Yellow feather chicken is a kind of traditional poultry in China. In recent years,labor shortages and diseases are two factors that affect production and health of yellow feather chicken. Using machine vision instead of manual monitoring of chickens and rapid identification of diseased chickens is a new research direction to solve the plight of poultry breeding. The symptoms of a diseased chicken mainly occurred in the eyes and comb which were mainly in the head. A method to recognize diseased chickens based on the head features was proposed. At first,totally 500 images of the healthy chickens and 236 images of the diseased ones were separately captured from the videos taken in the actual feeding environment composed the graphic base for the experiment. From each image,10 chicken areas with10 pixels × 10 pixels,three comb areas with 5 pixels × 5 pixels and 10 background areas with 10 pixels ×10 pixels were selected to form the sample sets. The R,G,B and H component values of each pixel in the sample sets were obtained to get color difference threshold of the background and H threshold of the comb and chicken. Segmentation of the yellow feather chicken could be completed by using the color difference threshold for removing the background and the H thresholds for the object regions. Combs and eyes and their contours were also obtained in HSV color model by the H threshold. Then distance d1 between any two points on the different contours of the combs was calculated. The points if d1 was less than the maximal side of the external rectangle of each comb were connected to make the two combs to be a whole.The external rectangle of the connected combs included the chicken head. A correcting method was to extend this external rectangle to both sides until the width of the rectangle was larger than the height to improve the integrity of the chicken head recognition. Co-occurrence matrix of H component was calculated from the comb to get the color feature and the texture feature including ASM,COR,IDM,Ent 6 geometry feat

关 键 词：机器视觉 病鸡识别 鸡头修正算法 共生特征矩 平均识别算法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]