• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE International Conference on Mechatronics and Automation; 20060625-28; Luouang(CN) >Efficient Target Detection from Infrared Image Sequences Using the Sequential Monte Carlo Method
【24h】

Efficient Target Detection from Infrared Image Sequences Using the Sequential Monte Carlo Method

机译：使用顺序蒙特卡洛方法从红外图像序列进行有效目标检测

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 presents an efficient target detection algorithm from a sequence of infrared images using the sequential Monte Carlo method (SMC). The algorithm employs an evolution process of the particles which correspond to the candidates of the target position and whose evolution is controlled by the weight of the target feature. Through the iterative process on the differential images, a valve of the particle set is proposed to decide if there is a target in the image, and the state of the particle set is used to position the target. The experimental results demonstrated that the algorithm can detect the target with sea-sky background effectively regardless of the existence of serious non-Gaussian noises. The experiments also showed real-time efficiency of the algorithm for target detection.
机译：本文提出了一种有效的目标检测算法，该算法使用顺序蒙特卡罗方法（SMC）从一系列红外图像中进行检测。该算法采用了与目标位置的候选相对应的粒子的演化过程，其演化由目标特征的权重控制。通过对差分图像的迭代处理，提出了粒子集的阀来确定图像中是否存在目标，并使用粒子集的状态来定位目标。实验结果表明，无论是否存在严重的非高斯噪声，该算法都能有效地检测出具有海天背景的目标。实验还显示了目标检测算法的实时效率。

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