基于改进混合高斯背景模型的运动目标识别算法

Zhang Yongmei, Ma Li, Liu Mengmeng, S. Haiyan
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引用次数: 0

摘要

视频中的噪声、光照等突变因素容易导致运动目标识别误差。提出了一种基于改进混合高斯背景模型的船舶和车辆运动目标识别算法。该算法利用混合高斯背景模型和三帧差分,在运动扰动和背景光突变的情况下,获得背景较少的潜在目标区域,提取潜在区域的直线、形状因子和泽尼克矩特征,构造最小二乘支持向量机对船舶和车辆进行识别。实验结果表明,该算法能够准确地识别船舶和车辆。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Moving Target Recognition Algorithm Based on Improved Mixture Gaussian Background Model
Many mutant factors in the video such as noise and illumination can easily lead to the moving target recognition error. The paper proposes a moving target recognition algorithm based on improved mixture Gaussian background model for ships and vehicles. The algorithm on account of mixture Gaussian background model and three-frame difference can obtain the potential target regions with less background under the condition of motion disturbance and light mutation in the background, extract the straight line, shape factor and Zernike moment features from the potential regions, and construct the least square support vector machine to identify the ships and vehicles. The experiment results show the algorithm can accurately identify the ships and vehicles.
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