Vehicle detection using a magnetic field sensor

The measurement of vehicle magnetic moments and the results from use of a fluxgate magnetic sensor to actuate a lighting system from the magnetic fields of passing vehicles is reported. A typical U.S. automobile has a magnetic moment of about 200 A-m²(Ampere-meters²), while for a school bus it is about 2000 A-m². When the vehicle is modeled as an ideal magnetic dipole with a moment of 200 A-m², the predicted results from an analysis of the sensor-vehicle geometry agree closely with observations of the system response to automobiles.     

Temporal error concealment using motion field interpolation

An error concealment algorithm based on motion field interpolation is presented. For each pixel in a damaged block, the algorithm recovers a motion vector using bilinear interpolation of neighbouring motion vectors. This vector is then used to conceal the damaged pixel. Overlapped motion compensation is used to combine this algorithm with a boundary matching error concealment algorithm. Simulation results demonstrate the superior performance of the proposed algorithms     

微射流粒子场的同轴Fraunhofer全息测试

利用超短脉冲激光作为记录光源可以在瞬间将高速运动微粒“冻结”的原理,建立了同轴Fraunhofer远场全息测试系统,研究了在爆轰加载下物质的微射流现象。获取了清晰的高速运动微射流粒子场的全息图,通过激光再现给出了微射流粒子的分布、形状、尺寸速度等信息。     

Temporal error concealment using selective motion field interpolation

A temporal error concealment technique referred to as the selective motion field interpolation is investigated. Simulation was conducted on the H.263 codec and experimental results show that the proposed method significantly outperforms other concealment techniques     

Temporal image sequence prediction using motion field interpolation

A new method for motion-compensated temporal prediction of image sequences is proposed. Motion vector fields in natural scenes should possess two basic properties. First, the field should be smoothly varying within moving objects to compensate for nonrigid or rotational motion, and scaling of objects. Second, the field should be discontinuous along the boundaries of the objects. In the proposed method the motion vector field is modelled using finite element methods and interpolated using adaptive interpolators to satisfy the above-stated requirements. This is particularly important when only very sparse estimates of motion vector fields are available in the decoder due to bit-rate constraints limiting the amount of overhead information that can be transmitted. The proposed prediction method can be applied for low-bit-rate video coding in conventional codecs based on motion-compensated prediction and transform coding, as well as in model-based codecs. The performance of the proposed method is compared with standard motion-compensated prediction based on block matching. It is shown that for simple video telephony scenes a reduction of more than 30% in the energy of the prediction error can be achieved with an unchanged number of transmitted motion vectors and with only a modest increase in computational complexity. When implemented in an H.261 codec the new prediction method can improve the peak SNR 1–2 dB producing a significant visual improvement.     

Electron motion in a helically perturbed magnetic field

Exact solutions have been obtained for the equations of an electron subjected to a transverse rotating magnetic field superimposed on a homogeneous axial magnetic field. The solutions show that complete transfer of the axial energy into transverse energy is possible for a range of values of the injection velocity and the transverse magnetic field.     

Double compression detection based on local motion vector field analysis in static-background videos

Videos captured by stationary cameras are widely used in video surveillance and video conference. This kind of video often has static or gradually changed background. By analyzing the properties of static-background videos, this work presents a novel approach to detect double MPEG-4 compression based on local motion vector field analysis in static-background videos. For a given suspicious video, the local motion vector field is used to segment background regions in each frame. According to the segmentation of backgrounds and the motion strength of foregrounds, the modified prediction residual sequence is calculated, which retains robust fingerprints of double compression. After post-processing, the detection and GOP estimation results are obtained by applying the temporal periodic analysis method to the final feature sequence. Experimental results have demonstrated better robustness and efficiency of the proposed method in comparison to several state-of-the-art methods. Besides, the proposed method is more robust to various rate control modes.     

Symbol detection in spatial multiplexing system using particle swarm optimization meta-heuristics

Symbol detection in multi-input multi-output (MIMO) communication systems using different particle swarm optimization (PSO) algorithms is presented. This approach is particularly attractive as particle swarm intelligence is well suited for real-time applications, where low complexity and fast convergence is of absolute importance. While an optimal maximum likelihood (ML) detection using an exhaustive search method is prohibitively complex, PSO-assisted MIMO detection algorithms give near-optimal bit error rate (BER) performance with a significant reduction in ML complexity. The simulation results show that the proposed detectors give an acceptable BER performance and computational complexity trade-off in comparison with ML detection. These detection techniques show promising results for MIMO systems using high-order modulation schemes and more transmitting antennas where conventional ML detector becomes computationally non-practical to use. Hence, the proposed detectors are best suited for high-speed multi-antenna wireless communication systems. Copyright © 2008 John Wiley & Sons, Ltd.     

A low-complexity region-based video coder using backwardmorphological motion field segmentation

We introduce a novel region-based video compression framework based on morphology to efficiently capture motion correspondences between consecutive frames in an image sequence. Our coder is built on the observation that the motion field associated with typical image sequences can be segmented into component motion subfield "clusters" associated with distinct objects or regions in the scene, and further, that these clusters can be efficiently captured using morphological operators in a "backward" framework that avoids the need to send region shape information. Region segmentation is performed directly on the motion field by introducing a small "core" for each cluster that captures the essential features of the cluster and reliably represents its motion behavior. Cluster matching is used in lieu of the conventional block matching methods of standard video coders to define a cluster motion representation paradigm. Furthermore, a region-based pel-recursive approach is applied to find the refinement motion field for each cluster and the cluster motion prediction error image is coded by a novel adaptive scalar quantization method. Experimental results reveal a 10-20% reduction in prediction error energy and 1-3 dB gain in the final reconstructed peak signal-to-noise ratio (PSNR) over the standard MPEG-1 coder at typical bit rates of 500 Kb/s to 1 Mb/s on standard test sequences, while also requiring lower computational complexity.     

Low-bit-rate video coding using dense motion field and uncoveredbackground prediction

It is well known that accurate dense motion field can improve the video coding efficiency. This paper presents a novel Markov random field (MRF) model that estimates both the dense motion and uncovered background fields in image sequences, and the application of these estimates in H.263-based video coding framework.     

用于检测透明介质中微粒的光奇异滤波器的研究

本文报道我们研究设计的实时、平行处理像的光学奇异滤波器(Optical Novelty Filter)的原理与结构,以检测透明介质中的微粒为例,分析了影响处理结果的各种因素。利用这一滤波器可以检测出15μm以上尺寸的微粒,检测的重复性可达98.6％。     

The dependence of the motion of a charged particle on the phase of entry into the field of a high-intensity electromagnetic wave

The motion of charged particles in the field of a linearly polarized electromagnetic wave is studied. The phase trajectory of the motion projected on the planes corresponding to the longitudinal and transverse (with respect to the wave) directions is considered.     

Organ motion detection in CT images using opposite rays in fan-beamprojection systems

Motion artifacts have been identified as a problem in medical tomography systems. While computed tomography (CT) imaging has been getting faster, there remains a need to detect and compensate for motions in clinical follow-up of neurological patients (multiple sclerosis, tumors, stroke, etc.), in cardiac imaging, and in any area in which failing to detect a motion artifact may lead to misdiagnosis. We have developed a novel algorithm to detect motion in brain images. The algorithm deals with detecting and isolating motion in the object domain using only the information available in the sinogram domain. The new "opposite ray algorithm" (ORA) addresses the issue of motion in the interior elements of the object. The ORA combines information from projections that are opposite in space and separated in time to isolate and identify the motion. A sinogram of motion is created, integrated and reconstructed to isolate the moving component. The algorithm can be used with conventional clinical scanners employing quarter-detector offset. The significant effect of quarter-detector offset on the ORA is investigated. The effects that a finite beamwidth and noise have on the ORA are also investigated. Both the similarity index and a correlation coefficient are used to evaluate the algorithm. The algorithm is successful when applied to cases exhibiting translational and translational-rotational motion. A similarity index of 0.88 is obtained in a typical case with both translational and rotational motion. Further development is recommended in the deformation case.     

Contrast independent motion detection using 'inverse pair' spatio-temporal edge detectors

Detection of motion by methods such as background differencing is bedevilled by noise-induced changes which can appear as motion signals. It is therefore important to have methods which extract motion in a more fundamental way. To achieve this it is necessary to remember that motion is a spatio-temporal (3D) phenomenon. This problem is approached by applying 'inverse pair' filters, the outputs of which are combined to give a response which is invariant to contrast. The output response is also invariant to direction of motion within the image.     

微颗粒场同轴全息的离焦处理方法

一、引言 全息法自首次应用于微颗粒场的分析以来,得到了不断发展,初期工作主要对技术本身及其机理进行探讨。实验表明,全息法是测量三维微颗粒场的有效手段,具有景深大、不干扰粒子群,且能记录粒子的大小、位置及速度等优点,并得到了广泛应用。 全息法将微颗粒场的数据信息寓于图像之中,所以必须对微颗粒场的再现图像进行处理,以“读出”粒子群的几何信息(尺寸、分布等)。以往的工作大部分都是处理粒子的聚焦像,而对球形的微颗粒,也可由粒子的离焦像求取粒子的大小和分布。 本文将此法应用于微颗粒场的处理,用一套半自动的图像处理系统,用所设计的程序,对微颗粒场的同轴全息图再现的离焦像进行处理,得到粒子的几何信息。     

Monte Carlo particle simulation of a GaAs short-channel MESFET

A Monte Carlo particle simulation of a 0.25 ?m-long gate (and 0.25 ?m-long channel) GaAs MESFET having a practical doping density and sitting on a substrate is carried out. Extremely high values of gm and Idss of 643 mS/mm and 5.35 mA/20 ?m were obtained. The near-ballistic nature of the electron transport in the FET was confirmed.     

A CMOS-compatible DNA microarray using optical detection together with a highly sensitive nanometallic particle protocol

In this paper, we present a fully CMOS-compatible optical deoxyribonucleic acid (DNA) microarray based on a nanometallic particle detection protocol. Silver-enhanced gold nanoparticle binding in the DNA sample induces opacity, instead of fluorescence, of matching DNA strands on the microarray. The active pixel sensor CMOS chip transduces opacity to electrical form for random-access readout. This system has many unique features, including 1) it is fully compatible with the mainstream standard CMOS technology; 2) its use eliminates the costly external optical scanner; and 3) it is capable of working under ordinary light sources instead of bulky and highly specific UV light sources. Experimental results on the system demonstrate high sensitivity, with concentrations as low as 10 pM detected.     

People detection and tracking with multiple stereo cameras using particle filters

In this work, a novel approach for people detection and tracking using multiple stereo cameras is proposed. Our proposal consists in combining information from all the available cameras using three different plan-view maps. Occupancy and height maps register the volume and height of the objects that are visible in the stereo cameras, respectively. We also propose the use of a novel map, named confidence map, which registers the confidence of the information projected in each cell. The proposed confidence map is employed to fuse the information captured by each camera so that the most reliable information is kept in each cell. We then propose a particle filter algorithm for tracking people in the fused plan-view maps. The observation model employed considers height, occupancy and confidence information so that information from the most reliable camera is employed at each time instant. The experiments conducted show the validity of our proposal.