A video target detection algorithm based on pixels texture correlation background model

Jibin Fu, Xin Bai, Baode Ju
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引用次数: 3

Abstract

This paper describes a screen target detection algorithm which is based on the background of Pixel texture information to judge models. The model is based on Bayesian statistical model frame, using histogram to get background reference, and lead in texture information of pixels to determine the results of the test optimization. It can quickly and accurately generate reference background, accumulating less noise during the period of updating background, and keeping longtime stability. Experimental results show that compared with the Bayesian statistical model, the screen target detection algorithm which is based on the background of Pixel texture information to judge models has greatly improved in accuracy and reduced in error rate.
一种基于像素纹理相关背景模型的视频目标检测算法
本文提出了一种基于像素纹理信息背景判断模型的屏幕目标检测算法。该模型基于贝叶斯统计模型框架,利用直方图获取背景参考,并引入像素的纹理信息来确定测试优化结果。该方法能够快速准确地生成参考背景,在背景更新过程中积累的噪声较小,并保持长时间的稳定性。实验结果表明,与贝叶斯统计模型相比,基于像素纹理信息背景判断模型的屏幕目标检测算法在准确率上有较大提高,错误率降低。
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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