一种自适应的基于混合高斯模型的运动目标检测算法(英文)

Adaptive moving target detection algorithm based on Gaussian mixture model

为提高运动目标检测的可靠性,提出了一种自适应的基于混合高斯模型的运动目标检测算法.该算法利用混合高斯分布对每个背景像素建模,高斯分布的个数不是固定不变的,而是随着像素值的混乱程度自适应变化.差分图像的像素按大小被分为2部分,然后对这2部分分别进行自适应阈值化分割,得到前景图像.利用基于形态学重构的阴影消除方法来改善前景图像分割的性能.不同实际场景的实验结果表明该算法能够快速准确地建立背景模型,且具有更强的鲁棒性.

In order to enhance the reliability of the moving target detection, an adaptive moving target detection algorithm based on the Gaussian mixture model is proposed. This algorithm employs Gaussian mixture distributions in modeling the background of each pixel. As a result, the number of Gaussian distributions is not fixed but adaptively changes with the change of the pixel value frequency. The pixels of the difference image are divided into two parts according to their values. Then the two parts are separately segmented by the adaptive threshold, and finally the foreground image is obtained. The shadow elimination method based on morphological reconstruction is introduced to improve the performance of foreground image＇s segmentation. Experimental results show that the proposed algorithm can quickly and accurately build the background model and it is more robust in different real scenes.