• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Adaptive image segmentation using genetic and hybrid search methods
【24h】

Adaptive image segmentation using genetic and hybrid search methods

机译：使用遗传和混合搜索方法的自适应图像分割

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

This paper describes an adaptive approach for the important image processing problem of image segmentation that relies on learning from experience to adapt and improve the segmentation performance. The adaptive image segmentation system incorporates a feedback loop consisting of a machine learning subsystem, an image segmentation algorithm, and an evaluation component which determines segmentation quality. The machine learning component is based on genetic adaptation and uses (separately) a pure genetic algorithm (GA) and a hybrid of GA and hill climbing (HC). When the learning subsystem is based on pure genetics, the corresponding evaluation component is based on a vector of evaluation criteria. For the hybrid case, the system employs a scalar evaluation measure which is a weighted combination of the different criteria. Experimental results for pure genetic and hybrid search methods are presented using a representative database of outdoor TV imagery. The multiobjective optimization demonstrates the ability of the adaptive image segmentation system to provide high quality segmentation results in a minimal number of generations.
机译：本文介绍了一种针对图像分割的重要图像处理问题的自适应方法，该方法依赖于从经验中学习以适应和提高分割性能。自适应图像分割系统包含一个反馈环，该反馈环由机器学习子系统，图像分割算法和确定分割质量的评估组件组成。机器学习组件基于遗传适应，并（单独）使用纯遗传算法（GA）和GA与爬山（HC）的混合体。当学习子系统基于纯遗传学时，相应的评估组件将基于评估标准向量。对于混合情况，系统采用标量评估度量，该度量是不同标准的加权组合。使用室外电视图像的代表性数据库，提供了纯遗传搜索和混合搜索方法的实验结果。多目标优化证明了自适应图像分割系统能够以最少的代数提供高质量的分割结果。

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