A New Compact Omni-Directional Quasi-Self-Complementary Antenna for Wireless Communication Systems

This article describes a new miniaturized omni-directional antenna with quasi-self-complementary structure for wireless communication applications. A novel ground structure composed of five rectangular plates is proposed to enhance the impedance bandwidth and reduce the antenna size. The proposed antenna is comprised of two patches surrounded by the ground structure. Two metal patches of the antenna are located on two opposite sides of the dielectric substrate. The feed patch is used to excite the radiation patch. This unique design is realized by properly choosing the suitable feed patch shape, selecting similar slot shape on the radiation patch, and tuning their dimensions. The proposed antenna with an extremely small size of 6 mm × 9 mm has an operating impedance bandwidth ranging from 4.5 to 6.1 GHz for S11 < -10 dB, which also covers the two IEEE 802.11a wireless local area network bands (5.15 - 5.35 GHz and 5.725 - 5.825 GHz). In addition to be very small in size, the antenna exhibits omni-directional radiation patterns in the entire operating bandwidth and low cross polarization. The distortionless time domain performance of the antenna is confirmed by investigation of the phase response and group delay. The obtained results in both frequency and time domain show that the proposed antenna is suitable for use in wireless communication systems.

Design of Omni-Directional Tilt Sensor Based on Machine Vision

This paper presents a new Omni-Directional Tilt Sensor (ODTS), which consists of the LED light, transparent cone-shaped closed container, mercury, camera, embedded systems and so on. The volume of the mercury in the container is equal to half of the container’s. When the detected surface is horizontal, the shape of mercury in the image captured by the camera is a black disc since the mercury is lightproof. When the detected surface tilts, the mercury flows and the mercury surface always maintains horizontally due to the gravity force of the earth. At this time, some area of the transparent cone-shaped closed container is not shaded by mercury and the border of the mercury’s shape in the captured image is a half circle and a half ellipse. Thus there is a translucent crescent-shaped area in the image. With analyzing this area by the specific algorithm based on machine vision, the tilt angle and directional angle can be obtained. The experimental results show that the ODTS proposed has some advantages, such as simple maintenance, high precision, wide range, low cost, real-time, reliability and high visualization.

A Concept of Dynamically Reconfigurable Real-time Vision System for Autonomous Mobile Robotics

This paper describes specific constraints of vision systems that are dedicated to be embedded in mobile robots. If PC-based hardware architecture is convenient in this field because of its versatility, flexibility, performance, and cost, current real-time operating systems are not completely adapted to long processing with varying duration, and it is often necessary to oversize the system to guarantee fail-safe functioning. Also, interactions with other robotic tasks having more priority are difficult to handle. To answer this problem, we have developed a dynamically reconfigurable vision processing system, based on the innovative features of Cleopatre real-time applicative layer concerning scheduling and fault tolerance. This framework allows to define emergency and optional tasks to ensure a minimal quality of service for the other subsystems of the robot, while allowing to adapt dynamically vision processing chain to an exceptional overlasting vision process or processor overload. Thus, it allows a better cohabitation of several subsystems in a single hardware, and to develop less expensive but safe systems, as they will be designed for the regular case and not rare exceptional ones. Finally, it brings a new way to think and develop vision systems, with pairs of complementary operators.

Global Calibration Method of Multi-sensor Vision System Using Skew Laser Lines

Multi-sensor vision system plays an important role in the 3D measurement of large objects.However,due to the widely distribution of sensors,the problem of lacking common fields of view（FOV） arises frequently,which makes the global calibration of the vision system quite difficult.The primary existing solution relies on large-scale surveying equipments,which is ponderous and inconvenient for field calibrations.In this paper,a global calibration method of multi-sensor vision system is proposed and investigated.The proposed method utilizes pairs of skew laser lines,which are generated by a group of laser pointers,as the calibration objects.Each pair of skew laser lines provides a unique coordinate system in space which can be reconstructed in certain vision sensor＇s coordinates by using a planar pattern.Then the geometries of sensors are computed under rigid transformation constrains by taking coordinates of each skew lines pair as the intermediary.The method is applied on both visual cameras with synthetic data and a real two-camera vision system;results show the validity and good performance.The prime contribution of this paper is taking skew laser lines as the global calibration objects,which makes the method simple and flexible.The method need no expensive equipments and can be used in large-scale calibration.

Calibration of line structured light vision system based on camera’s projective center

Based on the characteristics of line structured light sensor, a speedy method for the calibration was established. With the coplanar reference target, the spacial pose between camera and optical plane can be calibrated by using of the camera’s projective center and the light’s information in the camera’s image surface. Without striction to the movement of the coplanar reference target and assistant adjustment equipment, this calibration method can be implemented. This method has been used and decreased the cost of calibration equipment, simplified the calibration procedure, improved calibration efficiency. Using experiment, the sensor can attain relative accuracy about 0.5%, which indicates the rationality and effectivity of this method.

Functional outcome of the low vision aids for visual impairment secondary to central nervous system tumors in children

To assess functional outcomes of optical low vision aids(LVAs) for pediatric visual impairment due to central nervous system(CNS) tumors. A prospective case study was conducted on 15 children with history of CNS tumors with mean age of 10.47±1.85 y. Lighthouse distance, near visual acuity tests, cycloplegic refraction, reading speed measurement and visual field examination were done. Prescription of far and near LVAs followed by training sessions. LVPrasad-functional vision questionnaire was done to evaluate performance. Visual impairment was moderate(13.3%), severe(73.3%), profound(6.7%) and near blindness in 6.7%. Telescopes prescribed in 33.4%, video magnifier in 46.7%. Questionnaire scores were significantly improved for distant rather than near tasks(P≤0.05) after training. LVAs rehabilitation is an effective method of improving vision in pediatric visual defects secondary to CNS tumors.

Influence of Data Clouds Fusion From 3D RealTime Vision System on Robotic Group Dead Reckoning in Unknown Terrain

This paper proposes the solution of tasks set required for autonomous robotic group behavior optimization during the mission on a distributed area in a cluttered hazardous terrain.The navigation scheme uses the benefits of the original real-time technical vision system(TVS)based on a dynamic triangulation principle.The method uses TVS output data with fuzzy logic rules processing for resolution stabilization.Based on previous researches,the dynamic communication network model is modified to implement the propagation of information with a feedback method for more stable data exchange inside the robotic group.According to the comparative analysis of approximation methods,in this paper authors are proposing to use two-steps post-processing path planning aiming to get a smooth and energy-saving trajectory.The article provides a wide range of studies and computational experiment results for different scenarios for evaluation of common cloud point influence on robotic motion planning.

A global vision system: using hue thresholds to exact feature and recognize

The fast paced nature of robotic soccer necessitates real time sensing coupled with quick behaving and decision making. In the field with real robots, it is important to well perceive the location of ball, team robots and opponent robots through the vision system in real time. In this paper the architecture of global vision system of our small size robotic team and the process of object recognition is described. According to the study on color distribution in different color space and quantitative investigation, a method which uses H (Hue) thresholds as the major thresholds to feature exact and recognize object in real time is presented.

Monocular Vision Based Boundary Avoidance for Non-Invasive Stray Control System for Cattle: A Conceptual Approach

Building fences to manage the cattle grazing can be very expensive;cost inefficient. These do not provide dynamic control over the area in which the cattle are grazing. Existing virtual fencing techniques for the control of herds of cattle, based on polygon coordinate definition of boundaries is limited in the area of land mass coverage and dynamism. This work seeks to develop a more robust and an improved monocular vision based boundary avoidance for non-invasive stray control system for cattle, with a view to increase land mass coverage in virtual fencing techniques and dynamism. The monocular vision based depth estimation will be modeled using concept of global Fourier Transform (FT) and local Wavelet Transform (WT) of image structure of scenes (boundaries). The magnitude of the global Fourier Transform gives the dominant orientations and textual patterns of the image;while the local Wavelet Transform gives the dominant spectral features of the image and their spatial distribution. Each scene picture or image is defined by features v, which contain the set of global (FT) and local (WT) statistics of the image. Scenes or boundaries distances are given by estimating the depth D by means of the image features v. Sound cues of intensity equivalent to the magnitude of the depth D are applied to the animal ears as stimuli. This brings about the desired control as animals tend to move away from uncomfortable sounds.

EyeScreen:A Vision-Based Gesture Interaction System

EyeScreen is a vision-based interaction system which provides a natural gesture interface for humancomputer interaction （HCI） by tracking human fingers and recognizing gestures. Multi-view video images are captured by two cameras facing a computer screen, which can be used to detect clicking actions of a fingertip and improve the recognition rate. The system enables users to directly interact with rendered objects on the screen. Robustness of the system has been verified by extensive experiments with different user scenarios. EyeScreen can be used in many applications such as intelligent interaction and digital entertainment.

Studies on Cold Workability Limits of Brass Using Machine Vision System and its Finite Element Analysis

Cold Workability limits of Brass were studied as a function of friction, aspect ratio and specimen geometry. Five standard shapes of the axis symmetric specimens of cylindrical with aspect ratios 1.0 and 1.5, ring, tapered and flanged were selected for the present investigation. Specimens were deformed in compression between two flat platens to predict the metal flow at room temperature. The longitudinal and oblique cracks were obtained as the two major modes of surface fractures. Cylindrical and ring specimen shows the oblique surface crack while the tapered and flanged shows the longitudinal crack. Machine Vision system using PC based video recording with a CCD camera was used to analyze the deformation of 4 X 4 mm square grid marked at mid plane of the specimen. The strain paths obtained from different specimens exhibited nonlinearity from the beginning to the end of the strain path. The circumferential stress component Os increasingly becomes tensile with continued deformation. On the other hand the axial stress Oz , increased in the very initial stages of deformation but started becoming less compressive immediately as barreling develops. The nature of hydrostatic stress on the rim of the flanged specimen was found to be tensile. Finite element software ANSYS has been applied for the analysis of the upset forming process. When the stress values obtained from finite element analysis were compared to the measurements of grids using Machine Vision system it was found that they were in close proximity.

A Programmable High Speed Vision System with Superscalar PE and Its Parallel Computing Language

Pixel-parallel PE and SIMD architectures are widely used in high-speed image processing to enhance computing power. With fully exploiting the data level parallelism of low- and middle-level image processing, SIMD architecture is able to finish great amount of computation with much less instruction cycle thus satisfy the high-speed system requirement. The main computation parts in those SIMD image processing hardware is known as PE (processing element) and it is responsible for transferring, storing and processing the image data. This paper describes a high-speed vision system with superscalar PE to enhance system performance and its dedicated parallel computing language specifically devel-oped for this vision system. The vision system can achieve motion detection at more than 2000fps and face detection at more than 100 fps which overwhelms some general serial CPUs in the same applications.

基于LabVIEW和IMAQ Vision的目标统计系统

为了提高目标统计的速度和准确度,提出了一个基于LabVIEW(laboratory virtual instrument engineering workbench)和IMAQ(image acquisition)Vision软件包的目标统计系统。其基本思想是首先对采集到的目标图像二值化,然后依次利用移除小目标、腐蚀以及分离目标模块将图像中的粘连目标分离,并尽可能保留残缺目标细节,最后通过统计模块实现目标数量统计。实验结果表明该目标数量统计系统具有较好的实时性和准确性。

无人机GPS/SINS/Vision组合导航技术

针对无人机GPS/SINS组合导航系统中航向角误差可观测性差的问题,提出了一种无人机GPS/SINS/Vision组合导航方法。使用无人机搭载的摄像机获取周围景物的图像序列,通过跟踪图像序列中提取的特征点,利用极几何约束获得其间摄像机的位移信息,将测量到的位移信息融合到GPS/SINS组合导航系统中,构成GPS/SINS/Vision组合导航系统。通过观测位置误差、速度误差和摄像机位移在像平面上的投影误差,建立组合导航误差状态卡尔曼滤波器,估计导航系统的误差状态,并根据估计结果对导航系统状态进行修正。推导了滤波器状态方程和测量方程,使用Simulink对算法进行仿真验证,在水平姿态角偏差为10°左右、航向角偏差为20°左右的初始条件下,水平姿态角误差和航向角误差均能快速收敛,水平姿态角误差在10s后收敛到1°左右,航向角误差20 s后收敛到2°以内。仿真实验表明,该方法能有效提高无人机姿态角估计的速度和精度。

Study on the Changes of China's Water Right System

Irrigation was developed in ancient China.The management of water resources has existed since ancient times when the embryonic form of water right system was established.From perspectives of environmental law,the water rights system in ancient China,especially the water rights system after Ming Dynasty,gave no explicit concept to water rights,but the participatory management of water users was included in implementation.Such management had the same connotation with the modern concept of water rights and thereby it has an instructional significance to perfect the water rights system of in modern China.

Advances in Vision-Based Lane Detection：Algorithms,Integration,Assessment,and Perspectives on ACP-Based Parallel Vision

Lane detection is a fundamental aspect of most current advanced driver assistance systems(ADASs). A large number of existing results focus on the study of vision-based lane detection methods due to the extensive knowledge background and the low-cost of camera devices. In this paper, previous visionbased lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods. Next, considering the inevitable limitations that exist in the camera-based lane detection system, the system integration methodologies for constructing more robust detection systems are reviewed and analyzed. The integration methods are further divided into three levels, namely, algorithm, system,and sensor. Algorithm level combines different lane detection algorithms while system level integrates other object detection systems to comprehensively detect lane positions. Sensor level uses multi-modal sensors to build a robust lane recognition system. In view of the complexity of evaluating the detection system, and the lack of common evaluation procedure and uniform metrics in past studies, the existing evaluation methods and metrics are analyzed and classified to propose a better evaluation of the lane detection system. Next, a comparison of representative studies is performed. Finally, a discussion on the limitations of current lane detection systems and the future developing trends toward an Artificial Society, Computational experiment-based parallel lane detection framework is proposed.

Dynamic Coordination of Uncalibrated Hand/Eye Robotic System Based on Neural Network

A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.

Earth Vision地质建模辅助系统的设计及应用

Earth Vision是在油田地质研究中应用十分广泛的建模软件,鉴于在进行地质建模时,前期的数据准备工作是一项烦琐而且容易出错的重复性工作,利用Visual Basic编程工具设计了Earth Vision地质建模辅助系统。该系统不仅使建模数据的准备过程实现程序化,同时补充和完善了Earth Vision建模软件的一些功能。该系统操作简便,针对Earth Vision建模软件设计,具有广泛的适用性,成功应用在埕岛油田和孤岛油田的地质研究工作中,取得了较好效果。

GPS/VISNAV integrated relative navigation and attitude determination system for ultra-close spacecraft formation flying

For the improvement of accuracy and better fault-tolerant performance, a global position system （GPS）/vision navigation （VISNAV） integrated relative navigation and attitude determination approach is presented for ultra-close spacecraft formation flying. Onboard GPS and VISNAV system are adopted and a federal Kalman filter architecture is used for the total navigation system design. Simulation results indicate that the integrated system can provide a total improvement of relative navigation and attitude estimation performance in accuracy and fault-tolerance.

Application of Machine Vision to Vehicle Automatic Collision Warning Algorithm

Using the new technologies such as information technology, communication technology and electronic control technology, vehicle collision warning system（CWS） can acquire road condition, adjacent vehicle march condition as well as its dynamics performance continuously, then it can forecast the oncoming potential collision and give a warning. Based on the analysis of driver＇s driving behavior, algorithm＇s warning norms are determined. Based on warning norms adopting machine vision method, the cooperation collision warning algorithm（CWA） model with multi-input and multi-output is established which is used in supporting vehicle CWS. The CWA is tested using the actual data and the result shows that this algorithm can identify and carry out warning for vehicle collision efficiently, which has important meaning for improving the vehicle travel safety.