广东工业大学学报 ›› 2013, Vol. 30 ›› Issue (4): 88-92.doi: 10.3969/j.issn.1007-7162.2013.04.016

• 综合研究 • 上一篇    下一篇

基于SVM的二叉树羽毛片颜色分类器

朱颖,汪仁煌,李宁,李逸岳   

  1. 广东工业大学 自动化学院, 广东 广州 510006
  • 收稿日期:2012-09-11 出版日期:2013-12-30 发布日期:2013-12-30
  • 作者简介:朱颖(1986-),女,硕士研究生,主要研究方向为机器视觉、图像处理.

A Binary Tree Classifier for Feather Color Based on SVM

Zhu Ying, Wang Ren-huang, Li Ning, Li Yi-yue   

  1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2012-09-11 Online:2013-12-30 Published:2013-12-30

摘要: 为提高羽毛片生产效率和质量,减少主观分级误差,提出了一种利用机器视觉对羽毛片颜色自动分级的方法.首先在YU′V′颜色空间的基础上,对图像的特征值进行了提取与分析;然后结合特征值构建了一种基于SVM的二叉树多类分类器对羽毛片颜色进行分类,并分析了其分类误差.实验结果表明:该分类器正确率高,可有效确定羽毛片颜色的级别,满足羽毛片自动分级的生产要求.

关键词: 机器视觉;羽毛片;颜色空间;SVM;二叉树;多类分离器

Abstract: In order to increase productivity, reduce subjective grading error and improve quality, it proposed a method of using machine vision for automatic ratings of feather color. First, the eigenvalues of images were extracted and analyzed, based on the YU‘V’ color space. Then, an optimized binary tree of multiclass classifiers was built, based on SVM, combined with its characteristic value. It was used to classify the feather color. Finally, the classification error was analyzed. The experimental results show that the designed classifier has a high correct rate, and that it can efficiently determine the feather color level, thus satisfying the production requirement for automatic grading of feather.

Key words: machine vision; feather; color space; SVM; binary tree;multiclass classifiers

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