国防科技大学学报2013，Vol.35Issue(1)：103-107,5.
低信噪比下融合随机共振的运动目标检测算法
An algorithm improving objects detection for low-quality video using stochastic resonance
陈明生 1秦明新 1孙即祥 1尹中秋 1宁旭1
作者信息
摘要
Abstract
Video object extraction is a key technology in intelligence surveillance. An object detection algorithm for low - quality video based on Gaussian Mix Model and stochastic resonance was proposed. Firstly, the algorithm generated the object probability gray image from the current frame with the Gaussian Mix Model by the mapping function defined. Then, stochastic resonance was applied to the object probability gray image by adding noise until the defined evaluation function achieved the minimum value. After stochastic resonance, an effectively enhanced object probability gray image could be obtained. Hence the binary image including the interested objects is retrieved by segmentation of the enhanced object probability gray image. The experimental results show that the proposed algorithm combining the Gaussian Mix Model and the stochastic resonance achieved satisfactory subjective and objective performance under the worse environment with dark, foggy and infrared imaging while the classic background subtraction method almost could not detect the interested objects.关键词
目标检测/混合高斯/目标概率灰度图/随机共振Key words
object detection/ Gaussian mixture model/ object probability gray image/ stochastic resonance分类
信息技术与安全科学引用本文复制引用
陈明生,秦明新,孙即祥,尹中秋,宁旭..低信噪比下融合随机共振的运动目标检测算法[J].国防科技大学学报,2013,35(1):103-107,5.
