快速消除车辆阴影的多阈值图像分割法

 视频图像分割时的运动阴影由于与被测对象的相似性而常被误判为被测对象,传统的阴影检测方法一般难以满足实时智能交通系统对处理速度的要求。为此,提出用多阈值法分割图像,将灰度化的当前图像与背景差分,再用正、负两个阈值对其二值化,在分割出深色和浅色被测对象的同时消除阴影。实验表明,将这种方法应用于运动车辆的检测,具有速度快和阴影消除效果好等特点,可应用于实时的运动目标检测和跟踪等领域。     

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.     

Adaptive threshold selection for background removal in fringe projection profilometry

In fringe projection profilometry, background and shadow are inevitable in the image of an object, and must be identified and removed. In existing methods, it is nontrivial to determine a proper threshold to segment the background and shadow regions, especially when the gray-level histogram of the image is close to unimodal, and an improper threshold generally results in misclassification of the object and the background/shadow. In this paper, an adaptive threshold method is proposed to tackle the problem. Different from the existing automatic methods, the modulation-level histogram, instead of the gray-level histogram, of the image is employed to determine the threshold. Furthermore, a new weighting factor is proposed to improve Otsu's method to segment the image with a histogram close to unimodal, and the modulation difference of the object pixels and the background/shadow pixels is intensified significantly by the weighting factor. Moreover, the weighting factor is adaptive to the image. The proposed method outperforms existing methods either in accuracy, efficiency or automation. Experimental results are given to demonstrate the feasibility and effectiveness of the proposed method.     

Human detection based on motion object extraction and head–shoulder feature

Aimed at the shortcomings of the traditional video monitoring system, human detection method in intelligent video monitoring system was researched. This paper proposed a human detection method based on motion object extraction and head–shoulder feature to complete human detection and statistics in video image sequences. Firstly, background subtraction based on adaptive threshold was used to extract foreground moving object information, then image erosion and image dilation were used to bypass the object shade and remove false object in order to optimize the results of motion object extraction. And finally, for realizing human moving object detection, we proposed the object discrimination algorithm based on human head–shoulder feature to complete human detection and statistics. Experimental results show that the method can successfully realize human detection and statistics. The method is highly accurate and has good real-time and extensive applications. The identification rate is 86% through human video sequences to test. This method can detect human automatically and provide the theoretical and technological base for object detection in the intelligent surveillance system.     

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.     

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.     

Structure of odd–odd La at high spin

The high spin states in the N=79 odd–odd ¹³⁶La nucleus have been investigated by in-beam γ-spectroscopic techniques following the ¹³⁰Te(¹¹B, 5n)¹³⁶La reaction at E=52 MeV using an array, consisting of eight Compton-suppressed clover germanium detectors. Thirty nine new γ rays have been assigned to ¹³⁶La on the basis of γ ray singles and γγ-coincidence data. The level scheme of ¹³⁶La has been extended above the known 115 ms isomer upto an excitation energy of 4.6 MeV and spin 18. Thirty one new levels have been proposed and spin-parity assignments for most of the newly proposed levels have been made on the basis of the deduced asymmetry ratios and polarisation information for the de-exciting transitions. The observed positive parity yrast band has been compared with the theoretical calculation, done within the framework of particle rotor coupling model (PRM) where the two odd quasi-particles are coupled to an axially symmetric core. The level structure has been discussed in the light of the known systematics of the neighbouring N=79 isotonic nuclei.     

Fourier transform profilometry based on composite structured light pattern

In Fourier transform profilometry (FTP), the zero frequency of the imaged patterns will influence the measurement range and precision. The π phase shifting technique is usually used to eliminate the zero order component, but this method requires the capture of two fringe patterns with a π phase difference between them, which will impede the real time application of the method. In this paper, a novel method is proposed, in which a composite structured light pattern is projected onto the object. The composite structured light pattern is formed by modulating two separate fringe patterns with a π phase difference along the orthogonal direction of the two distinct carrier frequencies. This method can eliminate the zero frequency by using only one fringe pattern. Experiments show that there is no decrease in the precision of this novel method compared with the traditional π phase shifting technique.     

基于随机聚类的复杂背景建模与前景检测算法

为了构建鲁棒的背景模型和提高前景目标检测的准确性, 综合考虑同一位置的像素点在时间上的关联性和与其相邻像素的空间关联性, 基于经典的ViBe算法中的随机聚类思想提出了一种复杂背景建模和前景检测方法. 利用样本一致性原理, 采用前n帧序列图像得到初始化背景, 避免了Ghost现象的发生; 根据实际复杂背景的动态反馈获取自适应聚类阈值和自适应更新阈值进行随机聚类, 从而实现了对动态背景的适应性; 通过全局扰动阈值和局部像素级判断阈值的结合, 实现了对光照缓慢变化、快速变化以及突然变化的免疫性, 准确地分割前景目标. 对多组数据集的测试结果表明, 本文算法较大地提高了背景模型对动态背景、光照变化及相机抖动的复杂背景的适应性和鲁棒性. 算法还能很好地适用于红外图像检测运动目标的场合, 扩展了本算法的应用范围. 在没有进行任何图像预处理和形态学后处理情况下, 得到的原始前景检测精度优于其他对比算法.     

非制冷热像观瞄系统动态目标的智能检测

为了适应实时性的要求,在目标检测及定位时对处理方法的简洁性提出了很高的要求。基于热像观瞄系统,根据观瞄的目的,介绍了一种具有一定大小的目标检测方法。根据差分图像像素特性,提出了自适应选取阈值的新方法,对目标像素的亮度和分布密度进行精确定位。这种方法充分考虑了像素的自身属性信息,便于硬件的实时处理。该方法可以达到较高的检测率。     

Motion detection in moving background using a novel algorithm based on image features guiding self-adaptive Sequential Similarity Detection Algorithm

A novel efficient algorithm for motion detection in dynamic background was proposed. In image registration step, a feature-based and self-adaptive Sequential Similarity Detection Algorithm (SSDA) algorithm was proposed, which searches for matching position under constraints induced by image features with variational threshold. Then perform change detection by calculating and classifying the Mean Absolute Difference (MAD) around detected features in the middle frames of three consecutive images. Moving objects position was determined according to the rule that the feature from moving regions shows a lager MAD. Experiments on data sets of four typical scenes show that the improved registration algorithm is accurate and costs less than 0.4 s in computation, much faster compared with other four methods, and the proposed Dual Maximum Mean Absolute Difference Algorithm (DMMADA) can obtain a robust set of moving object features. Our algorithm can be used for fast detection of moving targets in dynamic background as well as change detection.     

真实场景下视频运动目标自动提取方法

视频运动目标跟踪逐渐成为研究热点并应用到军事民用等领域,为了能够从真实场景中快速准确地提取视频跟踪单运动目标或多运动目标,提出了一种新的运动目标自动提取方法。首先通过自适应阈值获得滤波后的相邻帧差值图像。其次,为了消除差值图像中噪声的影响,标记此二值图像的连通像素来检测出运动目标所在的区域,并与边缘检测出的空间信息结果比较得到运动目标模型。最后,将图像分成若干区域,在每个分区域内依次连接每个运动目标模型的最外围轮廓点,由此构成目标闭合轮廓。利用得到的连续边界,对运动目标进行提取。实验结果表明,该算法能够有效地自动提取速度不同的单运动目标,同时能够提取多运动目标。     

Cross-sections for the formation of isomeric pair Ge through (n, 2n), (n, p) and (n, α) reactions measured over 13.73 MeV to 14.77 MeV and calculated from near threshold to 20 MeV neutron energies

The cross-sections for formation of isomeric pair, ⁷⁵Ge^m(σ_m) and ⁷⁵Ge^g(σ_g), through ⁷⁶Ge(n, 2n), ⁷⁵As(n, p) and ⁷⁸Se(n, α) reactions were measured at 13.73 MeV, 14.42 MeV and 14.77 MeV neutrons and also estimated using EMPIRE-II and TALYS codes over neutron energies from near threshold to 20 MeV. For each (n, 2n), (n, p) and (n, α) reaction, the cross-section initially increases with neutron energy, but starts decreasing as the neutron energy exceeds the respective threshold of (n, 3n), (n, pn) and (n, αn) reactions. The higher values of σ_m relative to σ_g reveal that the transitions of the excited ⁷⁵Ge from higher energy levels to metastable state (7⁺/2) are favored as compared to unstable ground state (1⁻/2). The present values of cross sections for formation of ⁷⁵Ge^m,g through (n, 2n) and (n, α) reactions are lower, and that of (n, p) reaction are higher compared to most of the corresponding literature cross-sections.     

Vehicle speed measurement based on gray constraint optical flow algorithm

Vehicle speed measurement (VSM) based on video images represents the development direction of speed measurement in the intelligent transportation systems (ITS). This paper presents a novel vehicle speed measurement method, which contains the improved three-frame difference algorithm and the proposed gray constraint optical flow algorithm. By the improved three-frame difference algorithm, the contour of moving vehicles can be detected exactly. Through the proposed gray constraint optical flow algorithm, the vehicle contour's optical flow value, which is the speed (pixels/s) of the vehicle in the image, can be computed accurately. Then, the velocity (km/h) of the vehicles is calculated by the optical flow value of the vehicle's contour and the corresponding ratio of the image pixels to the width of the road. The method can yield a better optical flow field by reducing the influence of changing lighting and shadow. Besides, it can reduce computation obviously, since it only calculates the moving target contour's optical flow value. Experimental comparisons between the method and other VSM methods show that the proposed approach has a satisfactory estimate of vehicle speed.     

序列图像中运动目标的自动提取方法

针对目标检测与跟踪领域中的运动目标自动提取问题,提出了一种新的运动目标自动提取方法.利用已有的图像帧滤波后初始化背景,并在运动目标检测过程中,利用检测结果,不断地自动更新背景.使用背景差法检测运动区域,并对差分图像进行动态阈值分割,以及边缘链接,使其边缘处于基本连续状态.在得到的二值图上,提取轮廓,并根据目标大小选择面积阈值,剔除由于噪音或者背景提取不干净造成的虚假轮廓,将得到的轮廓掩模图像与原图像做逻辑与运算,提取出目标.实验结果表明,该方法可以有效地提取出刚体或非刚体运动目标.     

基于生物视觉特征和视觉心理学的视频显著性检测算法

提出了一种空域和时域相结合的视频显著性检测算法.对单帧图像,受视觉皮层层次化感知特性和Gestalt视觉心理学的启发,提出了一种层次化的静态显著图检测方法.在底层,通过符合生物视觉特性的特征图像（双对立颜色特征及亮度特征图像）的非线性简化模型来合成特征图像,形成多个候选显著区域;在中层,根据矩阵的最小Frobenius-范数（F-范数）性质选取竞争力最强的候选显著区域作为局部显著区域;在高层,利用Gestalt视觉心理学的核心理论,对在中层得到的局部显著区域进行整合,得到具有整体感知的空域显著图.对序列帧图像,基于运动目标在位置、运动幅度和运动方向一致性的假设,对Lucas-Kanade算法检测出的光流点进行二分类,排除噪声点的干扰,并利用光流点的运动幅度来衡量运动目标运动显著性.最后,基于人类视觉对动态信息与静态信息敏感度的差异提出了一种空域和时域显著图融合的通用模型.实验结果表明,该方法能够抑制视频背景中的噪声并且解决了运动目标稀疏等问题,能够较好地从复杂场景中检测出视频中的显著区域.     

Metal-oxide-semiconductor field effect transistor using ‘oxidizedμc-Si/ultrathin oxide’ gate structure

The metal-oxide-semiconductor (MOS) field effect transistor (FET) using ‘oxidized μ c-Si/ultrathin oxide’ gate structure was studied. It was found that this structure shows negative differential resistance behavior, which can be explained by the Coulomb blockade effect of trapped carriers and immediate tunneling into and tunneling out with gate bias variation. The requirements for the device with this structure showing negative differential resistance behavior are based on very weak resistive coupling between floating gate and channel. They are the thinness of the tunnel oxide film, the thickness ratio of the upper oxidized film and the tunnel oxide, and the channel threshold voltage. MOSFET with this gate structure is proposed as a new negative differential resistance device.     

Universal rise of hadronic total cross sections based on forward πp and scatterings

Recently there are several evidences of the increase of the total cross section σ_tot to be log²s consistent with the Froissart unitarity bound, and the COMPETE collaborations in the PDG have further assumed σ_totBlog²(s/s₀) to extend its universal rise with a common value of B for all the hadronic scatterings. However, there is no rigorous proof yet based only on QCD. Therefore, it is worthwhile to prove this universal rise of σ_tot even empirically. In this Letter we attempt to obtain the value of B for πp scattering, B_πp, with reasonable accuracy by taking into account the rich πp data in all the energy regions. We use the finite-energy sum rule (FESR) expressed in terms of the πp scattering data in the low and intermediate energies as a constraint between high-energy parameters. We then have searched for the simultaneous best fit to the σ_tot and ρ ratios, the ratios of the real to imaginary parts of the forward scattering amplitudes. The lower energy data are included in the integral of FESR, the more precisely determined is the non-leading term such as logs, and then helps to determine the leading terms like log²s. We have derived the value of B_πp as B_πp=0.311±0.044 mb. This value is to be compared with the value of B for scattering, B_pp, in our previous analysis [M. Ishida, K. Igi, Eur. Phys. J. C 52 (2007) 357], B_pp=0.289±0.023 mb. Thus, our result appears to support the universality hypothesis.     

基于灰度信息的动场景视频序列中运动对象的提取

提出了一种基于视频序列灰度信息的运动对象提取方法。该方法采用改进的Sobel算子提取边缘图像,依据边缘信息将视频图像分割为不同的灰度连续区域。在各灰度连续区域中,选取特征点进行匹配获得特征点对。根据特征点对合并灰度连续区域,获得全局运动参数。采用具有自适应帧间隔的帧差交集法,获得图像中运动对象区域。结合灰度信息和运动信息,分割出运动对象。实验结果表明,该算法可以有效地将运动对象从视频序列中提取出来。     

α-Decay calculations of medium mass nuclei within generalized density-dependent cluster model

The α-decay half-lives of even–even medium mass nuclei have been systematically investigated using a radial wave function within the generalized density-dependent cluster model. The α-decay width is calculated using the overlap integral of the quasi-bound initial state wave function, the scattering final state wave function, and the difference of potentials. The effective α–nucleus potential is constructed using the double-folded integral of realistic nucleon–nucleon interactions with the mass density distributions of α particles and daughter nuclei. For comparison calculations are also carried out for the Woods–Saxon shape potential. The present study is restricted to even–even nuclei with 82<N126, where the shell effect on the α-preformation factor has been taken into account for even–even N=126 isotones. The obtained α-decay half-lives are found to agree with the experimental data with a mean factor of less than 2 for both the double-folded potential and the Woods–Saxon shape potential.