基于并行隔帧差分光流场与灰度分析综合算法的运动目标检测

提出了隔帧差分的概念,并将其应用于光流场算法中,用改造后的隔帧差分光流场算法成功克服了传统光流场算法的不足(传统光流场算法不能识别帧间位移小于一个像元的运动目标).进一步对光流场计算结果与原始图像进行灰度综合分析,使目标的探测更加准确,减少了虚警和误判.采用不同间隔的序列差分构成并行识别系统结构,使整个系统能够探测各种不同速度的运动目标.实验结果表明:提出的运动目标检测算法能够准确有效地检测出不同速度的运动目标.     

一种有效的红外小目标检测方法

提出了一种基于中值滤波与梯度法的红外小目标检测方法.该方法首先通过中值滤波对红外图像进行平滑处理,接着采用背景差分技术将原始图像与经过中值滤波后的图像进行差分对消.在此基础上,再使用梯度锐化法对残差图像进行边缘信息的增强.最后,利用二值化处理凸显出目标点.该方法通过中值滤波与梯度法的互补效应实现了红外小目标的有效检测,仿真实验结果证明了该算法的有效性.     

A combined approach of Kullback–Leibler divergence and background subtraction for moving object detection in thermal video

In this work, a robust method for moving object detection in thermal video frames has been proposed by including Kullback–Leibler divergence (KLD) based threshold and background subtraction (BGS) technique. A trimmed-mean based background model has been developed that is capable enough to reduce noise or dynamic component of the background. This work assumed that each pixel has normally distributed. The KLD has computed between background pixel and a current pixel with the help of Gaussian mixture model. The proposed threshold is useful enough to classify the state of each pixel. The post-processing step uses morphological tool for edge linking, and then the flood-fill algorithm has applied for hole-filling, and finally the silhouette of targeted object has generated. The proposed methods run faster and have validated over various real-time based problematic thermal video sequences. In the experimental results, the average value of F₁-score, area under the curve, the percentage of correct classification, Matthew’s correlation coefficient show higher values whereas total error and percentage of the wrong classification show minimum values. Moreover, the proposed-1 method achieved higher accuracy and execution speed with minimum false alarm rate that has been compared with proposed-2 as well as considered peer methods in the real-time thermal video.     

连续帧间差分与背景差分相融合的运动目标检测方法

为了克服背景差分法和帧间差分法的不足,有效提高运动目标检测的准确性、实时性和检测效率,提出了一种将连续帧间差分法与背景差分法相结合的运动目标检测方法.首先通过连续帧间差分法获得连续帧差图像,然后分别通过线性的自适应滤波、非线性的中值滤波获得背景图像进行差分,之后再利用阈值分割技术实现运动目标的增强,从而有效解决背景差分法和帧间差分法中都可能出现的无法检测目标的现象.实验表明,该算法可以有效避免漏检、误检等情况,提高运动目标检测的效率和准确性.     

采用TMS320C6203的运动点目标检测系统设计

为了实现大视场运动点目标的实时检测和识别,设计了一种基于TMS320C6203为核心处理器件,FPGA为辅助控制处理器的硬件处理系统.在对点目标检测识别算法仿真实验分析的基础上,开发了实时运动点目标检测处理的软件系统.实验测试结果表明,该系统能够对信噪比不小于3dB,帧频为10fps的1024×1024运动点目标图像序列进行实时检测和识别,准确检测概率达到96%,满足实际工程要求.     

基于光流估计和自适应背景抑制的弱小目标检测

针对复杂云背景下的弱小目标探测,提出了一种基于光流估计和自适应背景抑制相结合的弱小目标检测算法.首先根据红外图像中云的移动规律,对云背景下的红外图像进行光流分析,提取运动云区.在光流场的计算中结合了云运动的特点以及光流方程的两个约束条件,对传统的基于梯度的光流法予以改进.同时发现移动云区对目标探测的影响较大,为了抑制移动云区对弱小目标的干扰,提出了自适应抑制复杂背景的算法,在光流场分析提取的移动云区中,利用代表背景复杂程度的背景因子,自适应调整分割阈值,抑制复杂背景的干扰.这样只在容易引起虚警的移动云区进行背景抑制处理,简化了计算量,降低了云区对弱小目标的干扰,减少了虚警和误判.实验结果表明该算法可以显著减少云区造成的虚警,并且能够探测出弱小目标.     

基于光流估计和自适应背景抑制的弱小目标检测

针对复杂云背景下的弱小目标探测,提出了一种基于光流估计和自适应背景抑制相结合的弱小目标检测算法.首先根据红外图像中云的移动规律,对云背景下的红外图像进行光流分析,提取运动云区.在光流场的计算中结合了云运动的特点以及光流方程的两个约束条件,对传统的基于梯度的光流法予以改进.同时发现移动云区对目标探测的影响较大,为了抑制移动云区对弱小目标的干扰,提出了自适应抑制复杂背景的算法,在光流场分析提取的移动云区中,利用代表背景复杂程度的背景因子,自适应调整分割阈值,抑制复杂背景的干扰.这样只在容易引起虚警的移动云区进行背景抑制处理,简化了计算量,降低了云区对弱小目标的干扰,减少了虚警和误判.实验结果表明该算法可以显著减少云区造成的虚警,并且能够探测出弱小目标.     

基于海天线的红外掠海小目标跟踪

针对红外掠海小目标对比度低,容易受到噪声、海面杂波、云层等干扰,导致跟踪失败的问题,提出了一种基于海天线的红外掠海小目标跟踪方法。通过对红外成像系统进行分析,利用拉普拉斯滤波抑制背景噪声,根据图像中海天线的位置信息,确定目标所在区域并进行目标检测。检测出可疑目标后,利用其灰度、尺寸、面积等特征信息,选出真实目标进行跟踪。实验结果表明,该算法对红外掠海小目标有很好的跟踪效果。     

辐射背景对岩石受力热红外光谱变化影响的实验研究

研究表明,岩石在加载过程中表面的红外辐射随应力发展而变化,而辐射信息的有效提取与辐射背景存在密切关系。通过理论分析不同实验环境对岩石受力热红外光谱变化影响,开展了花岗岩在室内外环境下的受力热红外光谱观测实验,分析了不同辐射背景下岩石红外辐射与应力的相关性以及由应力引发的辐射变化信息的强弱差异,并对两种环境下岩石应力热红外探测的优势波段进行了对比分析。结果表明,辐射背景对岩石受力热红外光谱探测结果有重要影响,室外环境因背景辐射较弱,相同应力作用下的红外辐射变化更加显著,与应力之间的相关程度更高,优势波段区间更宽,更加有利于岩石应力的热红外探测。8.0~11.8 μm波段是利用热红外遥感监测地表花岗岩应力变化的优势波段。     

Fisher’s linear discriminant ratio based threshold for moving human detection in thermal video

In video surveillance, the moving human detection in thermal video is a critical phase that filters out redundant information to extract relevant information. The moving object detection is applied on thermal video because it penetrate challenging problems such as dynamic issues of background and illumination variation. In this work, we have proposed a new background subtraction method using Fisher’s linear discriminant ratio based threshold. This threshold is investigated automatically during run-time for each pixel of every sequential frame. Automatically means to avoid the involvement of external source such as programmer or user for threshold selection. This threshold provides better pixel classification at run-time. This method handles problems generated due to multiple behavior of background more accurately using Fisher’s ratio. It maximizes the separation between object pixel and the background pixel. To check the efficacy, the performance of this work is observed in terms of various parameters depicted in analysis. The experimental results and their analysis demonstrated better performance of proposed method against considered peer methods.     

基于红外偏振特性的空间目标探测可行性探讨

红外偏振特性及其变化规律能够表征空间目标的表面信息与状态信息。结合当前偏振探测的最新进展,分析了基于红外偏振特性对空间目标进行探测的思路与可行性。由于空间目标偏振特性会随空间目标特定的材料以及运动轨道不同而存在差异,因此红外偏振探测技术可以为空间目标的探测和识别提供更多的依据。通过对空间目标常用的不同材料、同一材料不同表面状态以及在不同观测角下偏振特性的分析,得出光滑钢板红外平均偏振度是粗糙钢板的1.3倍左右。     

Moving object detection based on improved VIBE and graph cut optimization

Extracting foreground moving objects from video sequences is an important task and also a hot topic in computer vision and image processing. Segmentation results can be used in many object-based video applications such as object-based video coding, content-based video retrieval, intelligent video surveillance and video-based human–computer interaction. In this paper, we present a novel moving object detection method based on improved VIBE and graph cut method from monocular video sequences. Firstly, perform moving object detection for the current frame based on improved VIBE method to extract the background and foreground information; then obtain the clusters of foreground and background respectively using mean shift clustering on the background and foreground information; Third, initialize the S/T Network with corresponding image pixels as nodes (except S/T node); calculate the data and smoothness term of graph; finally, use max flow/minimum cut to segmentation S/T network to extract the motion objects. Experimental results on indoor and outdoor videos demonstrate the efficiency of our proposed method.     

基于稳健背景子空间的高光谱图像异常检测

在RX算法中,局部背景协方差矩阵估计会由于背景受到异常像元的“污染”而不能准确反映背景分布,从而导致检测性能下降.针对这一问题,提出一种基于稳健背景子空间的异常检测算法.利用空间秩深度度量背景中每个样本相对于整个背景样本分布空间的位置,将“游离”于背景分布空间之外的样本看作是潜在的异常样本,并将其映射到背景分布空间之内.在此基础上,通过估计背景的协方差矩阵,利用主成分分析构造能更精确地刻画背景的子空间,在该子空间进行了基于马氏距离的检测异常.模拟和真实数据验证了该算法的有效性.     

红外序列图像多运动目标检测

针对背景不动情况下提取红外图像运动目标,提出了一种基于连续四帧序列图像精确检测多运动目标的算法,并用软件仿真了该算法处理图像的效果并与其他方法进行了对比。经试验证明该方法算法简单,实时性好。对单目标、多目标、室内、室外、简单和复杂背景的红外序列都可以得到较好的检测效果。能够有效地去除背景和噪声,精确地确定运动目标位置,有利于后续的目标跟踪,算法适于实时应用。     

A wavefront aberrometer for dynamic high-order aberration measurement

This research studied the dynamic aberration of human eyes at near vision. A wavefront aberrometer was developed based on the Hartmann-Shack theory. This aberrometer can achieve dynamical aberration measurement of the human eye. The Aberrometer induces ocular accommodation by a moving target at near vision, and records the vision information of human eyes simultaneously during ocular accommodation process using a Hartmann-Shack sensor. Nineteen eyes of 10 volunteers are tested. Eighty-four percent eyes have induced accommodation amplitude between 3 diopter (D) and 8D. The highest induced accommodation amplitude is 8.6D. The aberrometer produces results with high precision and repeatability, i.e. an accuracy root-mean-square (RMS) of 1/50^λ and a repeatability RMS of 1/500^λ.