摘要
本文以基于静态背景下,对运动的物体进行识别、检测和跟踪,并鉴于软件编程的可实现性,在对图像进行预处理前提下,采用自适应高斯背景模型为静止背景下的图像序列提供背景图像,同时为了能更好的响应实际背景发生变化的情形,特别是对自适应背景,本文提出了算法上的改进和简化。
在图像预处理方面,主要分析了图像预处理处理方法,包括:中值滤波、维纳滤波、灰度处理、直方图均衡化技术,并对其进行了仿真。
在背景建立方面,通过对高斯背景模型的分析,对高斯模型加以改进,主要针对其方差和均值进行修改,变换样本均值和方差的计算方式,对其动态抽取样本,缩短取样时间和难度,尽快完成背景的初始化。
在目标检测方面,给出了运动目标检测与分割的仿真结果。在介绍了三种传统的运动目标检测算法的基本原理的基础上,运用帧间差分的方法,对目标进行提取,并对提取后的图像作出形态学处理,从而得到理想的目标提取图像。
在运动目标跟踪研究方面,本文从理论上分析卡尔曼滤波器的工作过程,基于人体运动特点和卡尔曼滤波的预测特性,提出一种基于人体中心的改进算法,提高预测的准确性,从而缩小搜索范围,减少搜索时间。
In this paper, based on a static background, the movement of objects to identify, detect and track, and in view of the software can be programmed to achieve, in the image of the pre-premise, adaptive Gaussian model for the background static background image Sequence to provide the background image, at the same time in order to be able to better respond to changes.
In the pre-image, the main image analysis of the pre-treatment, including: median filter, Wiener filter, to deal with gray, histogram equalization technology, and simulation.
In the context of the establishment, through the background of the Gaussian model analysis of the Gaussian model to improve, mainly for its mean and variance modified transform the sample mean and variance calculation, the dynamic of their sample to shorten the time sampling and the degree of difficulty as soon as possible to complete the background initialization.
In target detection, given the moving target detection and segmentation of the simulation results. After the introduction of the three traditional moving target detection algorithm based on the basic principle, the use of frame-difference approach to the extraction of targets, and after extracting the images to deal with morphology and thus be the ideal goal of extracting images.
Moving target in the follow-up study, this paper analyzed the work of the Kalman filter, based on the characteristics of human motion and Kalman filtering properties of the forecast, a human-based center for the Improvement of algorithms to improve the accuracy of the forecasts in order to reduce the scope of the search, the target of a search match.
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