• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>European Journal of Soil Biology >A method of green litchi recognition in natural environment based on improved LDA classifier
【24h】

A method of green litchi recognition in natural environment based on improved LDA classifier

机译：基于改进LDA分类器的自然环境绿荔枝识别方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Green litchi is always difficultly recognized by picking robot under the natural environment because of its similar color feature with background. A method of green litchi recognition based on improved LDA classifier is proposed by this paper. The color features of RGB components of litchi images were firstly analyzed. Then a linear discriminant analysis (LDA) method used for extracting convolutional features for classifying pixels of image was proposed to train the convolution kernel based on 1600 sample pixels. Simultaneously, an idea of 'maximal margin' from SVM to calculate the threshold of LDA classifier was introduced, and the corresponding threshold calculation method was put forward. The AdaBoost method was used in integration of a strong multiple LDA classifier. After classifying pixels, the Hough transform circle detection was used to locate the fruit of litchi by the sphere shape feature. Experiments with the proposed method show that green litchi recognition precision rate is 80.4% and the recall rate is 76.4%. This study provides technical support for the visual identification of green litchi and even other green fruits in natural environment. (C) 2017 Elsevier B.V. All rights reserved.
机译：由于其与背景类似的颜色特征，在自然环境下，通过挑选机器人难以认可绿荔枝。本文提出了一种基于改进的LDA分类器的绿荔枝识别方法。首先分析了荔枝图像的RGB组件的颜色特征。然后，提出用于提取用于分类图像像素的卷积特征的线性判别分析（LDA）方法，以训练卷积内核，基于1600个采样像素。同时，引入了从SVM到计算LDA分类器阈值的“最大边缘”的思想，并提出了相应的阈值计算方法。 adaboost方法用于集成强大的多LDA分类器。在分类像素之后，使用霍夫变换圆检测来定位荔枝的果实形状特征。所提出的方法的实验表明，绿荔枝识别精度率为80.4％，召回率为76.4％。本研究为绿荔枝甚至是自然环境中的其他绿色水果的视觉识别提供了技术支持。 （c）2017 Elsevier B.v.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号