基于自适应卡尔曼背景的动态背景下运动车辆分割方法

2011 IEEE 7th International Colloquium on Signal Processing and its Applications Pub Date : 2011-03-04 DOI:10.1109/CSPA.2011.5759918

K. Ahmad, Z. Saad, N. Abdullah, Z. Hussain, M. H. Mohd Noor

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引用次数: 8

摘要

本文引入自适应卡尔曼滤波对动态背景进行建模，进行背景相减。背景减法是一种识别目标的方法，在运动目标分割中非常常用。本文还对高斯减法、帧差法和近似中值法进行了比较研究。检测到的对象将显示在结果中。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Moving vehicle segmentation in a dynamic background using self-adaptive kalman background method

This paper introduce the adaptive kalman filter to modeling dynamic background for background subtraction. Background subtraction is a method to identify object and famous used in moving object segmentation. In this paper we also investigate a comparison study on Gaussian subtraction method, frame differencing method and approximate median method. The detection of object will be shown in the result.

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2011 IEEE 7th International Colloquium on Signal Processing and its Applications

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