【24h】

Detection of Moving Object: A Modular Wavelet Approach

机译:检测移动物体:模块化小波方法

获取原文
获取外文期刊封面目录资料

摘要

In video surveillance, identification is a very significant element for target tracking, activity recognition, traffic monitoring, military etc. The identification process classifies the pixels into either foreground or background and a common approach used to achieve such a classification is background removal. A Novel method is proposed for the moving object detection based on Modular Wavelet approach, where two consecutive image from image sequences are divided into four parts and then, the Wavelet Energy (WE) is applied to each sub image. The sub image in turn has two energy values of WE, namely, the percentage of energy corresponding to the approximation and the detail. Comparing the energy values corresponding to the detail, the moving object is recognized. Since the discrete wavelet transform has a pleasant property that it can divide an image into four different frequency bands without loss of the spatial information and most of the fake motions in the background can be decomposed into the high frequency wavelet sub-band. Proposed method is compared with existing methods and proposed algorithm gives an enhanced performance.
机译:在视频监控,识别是目标跟踪,行为识别,流量监控,军事等非常显著元素的识别过程划分的像素为前景或背景和用来实现这样的分类常用的方法是背景去除。提出了一种用于基于模块化小波的方法,其中从图像序列的两个连续的图像被划分成四个部分,然后将运动物体检测的新方法,所述小波能量(WE)被应用于每个子图像。反过来子图像具有WE的两个能量值,即,对应于近似和细节能量的百分比。比较对应于细节的能量值,运动对象被识别。因为离散小波变换具有令人愉悦的属性,它可以将图像划分为四个不同的频带,而不的空间信息丢失,最在后台假运动可以分解成高频小波子带。提出的方法与现有的方法相比,与提出的算法给出了一个增强的性能。

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