激光与光电子学进展, 2019, 56 (1): 011007, 网络出版: 2019-08-01   

基于改进视觉背景提取算法的运动目标检测方法 下载: 1289次

Moving Object Detection Algorithm Based on Improved Visual Background Extractor Algorithm
作者单位
天津城建大学计算机与信息工程学院, 天津 300384
摘要
针对视觉背景提取算法在复杂环境下检测出现鬼影现象、动态背景因素形成噪声干扰等问题,提出一种改进的视觉背景提取算法。通过创建辅助样本集,对复杂环境中像素点的重要特征信息进行收集;引入像素点鬼影因子和区域复杂度分析,自适应调节各像素点的匹配阈值和更新速率;最后通过基于滑动窗的像素点闪烁程度分析,将可能被误检为前景的噪声点向辅助样本中依概率更新。多场景下对比实验表明,该算法可将错分率降低至1.49%,且在检测时能快速消除鬼影现象,有效抑制动态背景产生的噪声干扰,同时保证前景目标能被完整识别,在复杂环境下的检测结果更加准确。
Abstract
Aim

ing at the problems of ghost and the noise interference from dynamic background in classic visual background extraction algorithm, an improved visual background extraction algorithm is proposed. The important feature information of pixels in complex environment can be collected by creating the auxiliary sample set. By introducing analysis of the pixel ghost factor and the region complexity, the matching threshold and updating rate of each pixel can be adaptively adjusted. With the pixel flicker analysis based on sliding window, the points which may be misdetected as foreground can be updated to the auxiliary samples according to probability. The comparative experiments in the multi-scene show that the proposed method can reduce the wrong classifications rate to as low as 1.49%, eliminate the ghost quickly, suppress the noise interference from the dynamic background, and ensure the complete recognition of foreground target. The results of the algorithm are more accurate in the complex environment.

王旭, 刘毅, 李国燕. 基于改进视觉背景提取算法的运动目标检测方法[J]. 激光与光电子学进展, 2019, 56(1): 011007. Xu Wang, Yi Liu, Guoyan Li. Moving Object Detection Algorithm Based on Improved Visual Background Extractor Algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(1): 011007.

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