红外预警卫星探测波段地球背景辐射仿真研究

针对红外预警卫星探测波段遥感数据难以获取的问题,研究了基于地表温度反演的红外预警卫星探测波段地球背景辐射仿真方法。采用了通用型单通道算法对FY-3/MERSI数据集进行地表温度反演,得到了全球地表温度分布图。在此基础上,构建了地表红外辐射模型,充分考虑了海拔、大气模式、地表类型等因素对地表辐射的影响,利用MATLAB与MODTRAN进行联合编程完成每个像元对应的地表辐射计算,实现了红外预警卫星探测波段地球背景辐射场景的图像生成。仿真结果表明:仿真图像分辨率高,能够准确反映红外预警卫星探测波段的地球背景辐射特性,可为研究红外预警卫星作战效能评估和目标识别技术提供场景数据支撑。     

基于级联和自适应子分类的目标检测方法

在基于机器学习的目标检测中,检测速度和检测准确性是主要考虑的问题。通过所设计的两级级联和自适应子分类的方法,有效提升了检测速度和检测的准确率。在实际检测时,可以通过一些简单的特征,快速否定绝大多数非检测目标的探测窗口,因此设计了两级级联的方法获得较高的检测速度:在两级级联的第一级采用一种快速简单的检测方法,快速地否定绝大多数错误的探测窗口,并使得几乎所有的正确的探测窗口通过第一级检测。在实际场景下,同一类目标常常有不同的表现形态,如不同姿势、颜色等,因此设计了自适应子分类的方法来获得较高的检测准确率:在两级级联的第二级通过对一类目标使用自动子分类的方法训练多个识别模型,在子分类过程中自动寻找最优分类方法,提升了识别的准确性。在利用著名的UIUC数据集以及一些高清图像的检测实验结果表明,该算法显著提升了检测速度和准确性。     

论红外成像系统的最大作用距离

作用距离是描述军用红外成像系统整机性能的一个重要参数。作用距离可以分为探测距离、识别距离和确认距离,其中以探测距离最大。根据红外成像系统、地球曲面和目标之间的几何关系,介绍了一种基于MATLAB的对地观察红外成像系统的最大作用距离计算方法。该值取决于整机所在高度、地球半径和目标高度。整机的实际探测距离或者对待研整机提出的作用距离指标不应该大于此值。     

基于trace特征的ISAR像空间目标识别

论文提出了一种基于trace特征的逆合成孔径雷达（Inverse Synthetic Aperture Radar,ISAR）像空间目标识别算法.首先将ISAR像进行分割与归一化处理,利用Canny边缘检测、Hough变换方法提取空间目标ISAR像最长轴,确保所提特征具有旋转不变性;然后仅对最长轴所在局部区域进行Trace变换生成空间目标ISAR像的局部trace矩阵,使得所提trace特征满足低维要求;再将trace矩阵每一列向量进行移位对准操作以消除ISAR像平移对识别带来的影响并将其作为空间目标识别的特征向量;最后在特征空间内以最小欧氏距离作为不相似度,采用集成分类器AdaBoost.M2-KNN完成了5类空间目标的分类识别.通过5类空间目标的ISAR数据对该方法进行目标识别验证,并与现有的几种ISAR像特征提取方法进行了对比.结果表明论文所提算法可行有效,可以明显地提高识别率.     

一种解决波动式干扰影响的序列图像运动目标检测方法

为解决复杂环境下的诸如枝叶摇摆、摄像机抖动等波动式干扰对运动目标检测的影响问题,该文提出基于视频窗口切分与分类的序列图像运动目标检测算法。首先将序列图像切分为rc大小的视频窗口,然后提取窗口内区域图像累积帧间差矩阵的简单统计特征,针对每一帧序列图像,将视频窗口进行分类,把它们划分为运动目标窗口和非运动目标窗口(包括静止背景窗口和波动式干扰窗口),最后将运动目标窗口合并为运动目标。该方法的优点是无需已知背景模型和运动目标大小、形状等任何先验信息。实验表明该算法能在摄像机抖动以及枝叶干扰等复杂环境下快速有效的检测出运动目标。     

Locating the eye in human face images using fractal dimensions

Facial feature extraction is an important step in many applications such as human face recognition, video conferencing, surveillance systems, human computer interfacing etc. The eye is the most important facial feature. A reliable and fast method for locating the eye pairs in an image is vital to many practical applications. A new method for locating eye pairs based on valley field detection and measurement of fractal dimensions is proposed. Possible eye candidates in an image with a complex background are identified by valley field detection. The eye candidates are then grouped to form eye pairs if their local properties for eyes are satisfied. Two eyes are matched if they have similar roughness and orientation as represented by fractal dimensions. A modified approach to estimating fractal dimensions that is less sensitive to lighting conditions and provides information about the orientation of an image under consideration is proposed. Possible eye pairs are further verified by comparing the fractal dimensions of the eye-pair window and the corresponding face region with the respective means of the fractal dimensions of the eye-pair windows and the face regions. The means of the fractal dimensions are obtained based on a number of facial images in a database. Experiments have shown that this approach is fast and reliable     

Method of radar detection and identification of metal and dielectric objects with resonant sizes located in dielectric medium

Mathematical model of a radar detection and identification system to be used for finding different objects buried in the ground or in other dielectric media is considered. In the suggested model scattering characteristics of 3D resonant objects are calculated by solving 2nd kind Fredholm integral equations for equivalent current densities on the object??s surface. Based on the obtained results we derive a method of detection and identification for specific types of objects which incorporates analysis of their natural resonant frequencies. Potentialities of the developed method for detection and identification of different types of mines are estimated.     

Gesture recognition for human–machine interaction in table tennis video based on deep semantic understanding

The analysis of moving objects in videos, especially the recognition of human motions and gestures, is attracting increasing emphasis in computer vision area. However, most existing video analysis methods do not take into account the effect of video semantic information. The topological information of the video image plays an important role in describing the association relationship of the image content, which will help to improve the discriminability of the video feature expression. Based on the above considerations, we propose a video semantic feature learning method that integrates image topological sparse coding with dynamic time warping algorithm to improve the gesture recognition in videos. This method divides video feature learning into two phases: semi-supervised video image feature learning and supervised optimization of video sequence features. Next, a distance weighting based dynamic time warping algorithm and K-nearest neighbor algorithm is leveraged to recognize gestures. We conduct comparative experiments on table tennis video dataset. The experimental results show that the proposed method is more discriminative to the expression of video features and can effectively improve the recognition rate of gestures in sports video.     

深度图像的目标潜在区域提取算法

目标检测和识别算法通常使用复杂特征以多尺度滑动窗的方式进行分析,运算效率往往非常低。因此,目标性被引入进行目标潜在区域的快速预判断,减少复杂特征需要分析的窗数,从而达到加速算法效率的目的。针对逐步普及的Kinect深度像机,该文提出了一种基于深度图像的目标性分析算法,以提升深度图像的目标检测识别算法的效率。首先基于深度图像的法向量,提出能够有效描述深度图像边缘信息的特征,然后通过支撑向量机学习目标性的分类器,以得分的形式给出候选区域中存在目标的概率,最后基于人眼的视觉机理对不同尺度的目标进行加权。通过深度图公共数据库的实验对比,该算法给定1000个候选区域时达到94.1%的召回率,保证了准确率的同时大大减少了区域数量,能有效的提升目标检测识别算法的效率。      

基于多级粒子窗的目标检测算法研究

针对滑动窗算法计算量较大的问题,提出一种多级粒子窗算法。首先构造一个目标分类器级联结构,然后在全图像域随机产生一组粒子,每一个粒子对应一个目标分类器。分类器的响应作为统计特征修正目标的似然概率密度函数,用于指导下一级的粒子生成,直至粒子收敛到稳定区域,从而实现对目标状态由粗到精的定位。分别将该方法用于单幅图像和图像序列中的目标检测,并与滑动窗算法进行了比较,结果表明,多级粒子窗算法能够快速精确实现目标检测。     

基于OpenCV的双摄像头活体人脸判定及实时跟踪系统

活体检测及人脸跟踪系统的构建已成为现代计算机视觉及OpenCV研究的热点。提出一种基于OpenCV的双摄像头活体人脸判定实时人脸跟踪系统。一种新的双摄像头活体人脸判定的方法,利用基于HAAR特征人脸检测算法,并判断距离。编写Windows程序调用串口API和下位单片机STC12C5410通信,采用CH341A芯片将RS232串口数据加载到USB协议数据栈中实现USB传输,单片机控制FUTABA舵机,获取上位机人脸检测坐标信息,实时调整舵机转动角度,使人脸始终处于图像中间290＊310阈值范围内,达到人脸跟踪。该系统结构精简,可作为模块用于门禁安保系统及构建其他机器人研究平台。     

基于梯度双面互补特性的级联快速目标检测

针对目标检测中精度和速度难以兼顾的问题,借助视觉注意理论中的目标感知与识别机制,分析目标描述中梯度幅值与梯度方向信息之间具有的互补性,提出了基于两层级联梯度特征的快速目标检测模型,可有效描述类无关和类相关检测器.一方面,采用梯度幅值特征,从滑动窗口采样中获得候选目标提议,大幅降低了验证窗口的数量,确保检测速度,另一方面,利用级联方式学习训练多个子检测器,可更好实现不同尺度变化下的目标检测精度.PASCAL数据集上的实验结果,解释了级联梯度特征对目标结构描述的有效性,表明了该文方法在与现有先进方法的检测精度相当的前提下,可极大提升检测速度.     

地球红外辐射背景成像方法研究

为模拟生成地球红外辐射背景图像,研究其成像方法。首先将地球表面划分为若干地表区域,考虑大气传输特性、地表类型、地袁经纬度及地袁海拔高度等因素影响,根据地袁类型,建立地球袁面区域温度模型和红外辐射亮度模型．然后运用数值计算方法得到地球表面温度和红外辐射亮度分布。根据红外探测器视角与视点．利用OpenGL实现了红外探测器在太空中对地球背景红外辐射亮度的三维图像显示。结果表明,模拟生成的地球红外背景图像效果逼真,可用于红外目标识别和仿真应用。     

A self-organizing approach to background subtraction for visual surveillance applications.

Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving objects provides a focus of attention for recognition, classification, and activity analysis, making these later steps more efficient. We propose an approach based on self organization through artificial neural networks, widely applied in human image processing systems and more generally in cognitive science. The proposed approach can handle scenes containing moving backgrounds, gradual illumination variations and camouflage, has no bootstrapping limitations, can include into the background model shadows cast by moving objects, and achieves robust detection for different types of videos taken with stationary cameras. We compare our method with other modeling techniques and report experimental results, both in terms of detection accuracy and in terms of processing speed, for color video sequences that represent typical situations critical for video surveillance systems.     

Distinguishing between natural and recolored images via lateral chromatic aberration

With the development of image colorization technique, the recolored images (RIs) become more and more authentic, making it very difficult to visually distinguish from natural images (NIs). Recently, researchers have proposed the detection methods towards recolored images. However, the current detection still has limitations such as poor generalization, large-scale training samples, high-dimensional features for training, and high computation cost. To address those issues, this paper proposes a novel method based on the lateral chromatic aberration (LCA) inconsistency and its statistical differences. Generally, RIs have fewer numbers of LCA characteristics than that of NIs, that inspire us to design the classifier for distinguishing two types of images. In particular, we propose to adopt very low 5-dimensional features to feed a classical SVM mechanism. The baseline ImageNet and Oxford datasets are used to verify the effectiveness of the proposed method, in which the performance of our proposed method rivals the prior arts.     

地球红外辐射背景成像方法研究

为模拟生成地球红外辐射背景图像, 研究其成像方法。首先将地球表面划分为若干地表区域,考虑大气传输特性、地表类型、地表经纬度及地表海拔高度等因素影响, 根据地表类型, 建立地球表面区域温度模型和红外辐射亮度模型, 然后运用数值计算方法得到地球表面温度和红外辐射亮度分布。根据红外探测器视角与视点,利用OpenGL 实现了红外探测器在太空中对地球背景红外辐射亮度的三维图像显示。结果表明, 模拟生成的地球红外背景图像效果逼真, 可用于红外目标识别和仿真应用。     

红外焦平面静态地平仪地面检测方法研究

本文针对红外焦平面静态地平仪的探测原理,就该地平仪的探测目标(地球及空间背景)在几何空间、辐射光谱及能量等物理层面的模拟方法进行了详细讨论,并在此基础上提出了设计带有大视场准直光学系统的地球模拟器和精密转台的地面测试方案.     

利用热红外偏振成像技术识别伪装目标

介绍了热红外偏振测量的原理,采用利用偏振信息在红外图像中识别伪装遮障的方法研制了一台热红外偏振成像仪,编写了偏振信息分析软件。利用该系统对地物背景（土壤）中的不同种类金属目标板及红外伪装遮障进行了热红外偏振成像探测实验。结果表明：在利用热红外偏振探测系统获得的Stokes矢量图中, 地物背景、金属目标板及红外伪装遮障的热红外偏振特性各不相同,并且和其红外辐射强度无关,相对红外强度探测更容易从地物背景中识别出金属目标板及红外伪装遮障。     

Efficient computation of local geometric moments

Local moments have attracted attention as local features in applications such as edge detection and texture segmentation. The main reason for this is that they are inherently integral-based features, so that their use reduces the effect of uncorrelated noise. The computation of local moments, when viewed as a neighborhood operation, can be interpreted as a convolution of the image with a set of masks. Nevertheless, moments computed inside overlapping windows are not independent and convolution does not take this fact into account. By introducing a matrix formulation and the concept of accumulation moments, this paper presents an algorithm which is computationally much more efficient than convolving and yet as simple.