查询词典 image detector

In order to bypass the difficulty of discretizing the boundary r or the Lebesgue discontinuous set Su in the Mumford-Shah model, we use an edge-detector function and a threshold value to induce a thin-belt where the image boundary lie in and displace the length of the boundary by the area of the thin-belt approximatively.

为避免在离散化Mumford-Shah模型中的边界Γ或Lebesgue不连续集S_u的困难，我们借助边界检测算子和门限值，确定图像边界所在的窄带区域，用窄带区域面积近似边界的长度。

Among them very multinomial and direct or indirect design reachs relevant industry to sensor, detailed situation is as follows: The computer reachs peripheral equipment: Hold pattern recognition of GPS receiver, graph and processing system; Microelectronics and photoelectron yuan parts of an apparatus: Cadmium of parts of an apparatus of coupling of CCD photoelectricity carry on one's shoulder, tellurium is mercuric , infra-red detector; CMOS image sensor; Communication equipment reachs a product: Smooth communication is metric with the instrument that monitor; Civil spacecraft reachs ground facilities: Spacecraft is lukewarm control a product; Automation machinery reachs device: Industrial robot and intelligent robot; Electromechanical key foundation: Intelligent air cylinder, intelligence changes model carapace breaker (voltage 380V, 660V, voltaic 1000A), prevent adopt device of dead apply the brake , the electron controls vehicle of the automatic gear-box, dynamoelectric steering gear that help strength, car to carry diagnostic system, gasoline engine electronic-controlled engine of device, derv is electronic-controlled car of device, alternative fuel changes device, car; Instrument appearance reachs a system: GPS car fixed position, monitoring calls the police attemper system, colliery installs all inspection to measure general management system, hydroelectric station to monitor control system, automatic cruise automatically to control a system (the car is auxiliary drive system), the electron collects fees administrative system (ceaseless car electron pays cost the system), two-phase; New-style medical apparatus and instruments: Medical sensor; Inorganic metalloid material: Component of the pottery and porcelain that suppress report, lukewarm characteristic thermal resistor ; New-style the sources of energy reachs equipment: The solar battery reachs package; The environment monitors an instrument: Monitor appearance, CO automatically to monitor appearance, automatic acid rain automatically sampler and determine appearance, soot, dust is automatic sampler and determine appearance, flue gas is automatic sampler and determine steam of end of appearance, car determines automatically appearance, portable poisonous and harmful gas determines quality of air of type of appearance, flow; The exploration of the sources of energy and mineral products resource develops device: MWD is followed get oil of logging instrument, numerical control monitor below well of deep well logging instrument, colliery reach calamity to forecast; The project measures and equipment of earthly physics observation: Project acceleration measures system, much general to strap weather radar (use be concerned with or double polarization technology), intelligence atmosphere sensor (contain lukewarm, press, irradiation level of wet, wind, precipitation, dew point, sun), personal computer control is automatic and perpendicular artesian well system , marine atmosphere; 1 2 of on one page issues one page

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An implementation for round object detector in the image by using the inner product detection methodology is proposed.

本文的目的是以向内积侦测演算法实现影像图片中圆形物体的侦测。

In the experiment the pre-processings, such as image filtering and Harris operator corner detector, etc. were used to get feature points quickly and realize the mapping transformation of camera parameters. The error estimate function was established to compare the proposed method with Tsai calibration algorithm.

实验过程中，利用图像降噪、改进的Harris算子角点提取等预处理过程快速提取特征点，实现摄像机参数标定的映射变换；建立了误差评价函数评价本文方法与Tsai标定算法。

In the experiment the preprocessings, such as image filtering and Harris operator corner detector, etc., were used to get feature points quickly and realize the mapping transformation of camera parameters. The error estimate function was established to compare the proposed method with Tsai calibration algorithm.

实验过程中，利用图像降噪、改进的Harris算子角点提取等预处理过程快速提取特征点，实现摄像机参数标定的映射变换；建立了误差评价函数评价本文方法与Tsai标定算法。

In this paper, the theory, algorithm, and experiment of automatic object detection and tracking are studied in depth. It is firstly pointed out that the essential of Mean Shift method is a special Newton-Gaussian method. A new method named Fast Mean Shift is established to stretch the conservative step of Mean Shift method. The convergence and validity of this new method are proved in theory. And it is also proved that the convergence speed of Fast Mean Shift is faster than that of Mean Shift. The contrast experiments of searching the maximum possibility density of random of data sets in plane and 3D space are done. The results show that this new method can reduce the iterations greatly. A new object tracking method based on Fast Mean Shift is built to improve the object tracking performance, which is shown in the face tracking experiment with the tennis sequence provided by the Ohio State University, and the car tracking experiment with the car sequence provided by Kalsruhe University. The face trcking experiment with highly noised images show that the object tracking method based on Fast Mean Shift has strong anti-jamming ability. A new fast color object detection technology based on characteristic color is established, which use characteristic color distribution to compute the characteristic color vector of any area in an image quickly. With the high performance search method, the fast object detection is achieved. At last, using object tracker based on Fast Mean Shift and color object detector based on characteristic color with the Kalman filter, PID controller, searial communication and other technologies, automatic object detection and tracking system with control system is built. The availability and anti-jamming ability of this system are verified by some object detection and tracking tests in different scenes.

本文对目标自动识别与跟踪进行了理论、计算、试验三方面的深入研究，主要包括：首次指出了目标跟踪技术中常用的均值迁移方法的本质为一种特殊的高斯-牛顿方法，改进了均值迁移方法步长取值保守的弱点，建立了快速均值迁移方法，证明了该方法的收敛性、有效性以及收敛速度优于均值迁移方法；进行了平面和3维随机分布数据集的最大概率密度搜索对比试验，试验结果表明，快速均值迁移方法大大减少了迭代次数；建立了基于快速均值迁移的目标跟踪方法，利用俄亥俄州立大学提供的乒乓球序列图像和卡斯鲁厄大学的汽车序列图像，对人脸和汽车目标跟踪性能分别进行了对比试验，并进行了高噪声人脸图像目标跟踪试验，结果表明，基于快速均值迁移的目标跟踪方法有效提高了目标跟踪性能，具有很强的抗干扰能力；建立了一种新型彩色目标自动识别方法，采用特征色彩分布函数实现了对任意图像区域特征色彩矢量的快速计算，建立了高效的搜索方法，实现了彩色目标的快速识别；将基于快速均值迁移方法的目标跟踪方法、基于特征色彩的目标识别方法与卡尔曼滤波、PID控制、串行通讯等技术结合，建立了带有控制系统的快速目标自动识别与跟踪系统，并在不同场景下进行了目标自动识别与跟踪试验，验证了快速目标自动识别与跟踪系统的有效性和抗干扰能力。

Moreover, the measurement and analyses of thermal image is made with the finished pyroelectric infrared array detector.

可明显看出因热绝缘结构的使用，使得元件在电性方面获得良好的提升。

An target detector can enable one to detect targets whose signatures are spectrally distinct from their surroundings with no a priori knowledge, and so ti becomes increasingly important in hyperspectral image analysis.

目标检测算法能够在没有先验光谱信息的情况下检测到与周围环境存在光谱差异的目标，具有较强的实用性，并成为了一个重要的研究热点。

In case of simple background, we use image difference for motion region detection, and then adopt the original Chan-Vese model for face contour detection and tracking, while in case of complex background, we use Wronskian change detector for motion region detection, and then adopt the modified Chan-Vese model for face contour detection and tracking.

对于简单背景情况，首先利用图像差分进行运动区域检测，然后在运动区域内采用Chan-Vese模型检测人脸轮廓，并根据其定位结果计算下一帧中新的运动区域和提取人脸轮廓；对于背景复杂的情况，则用朗斯基变化检测算子来首先检测出运动区域，然后在运动区域内采用改进的Chan-Vese模型检测人脸轮廓，并根据其定位结果计算下一帧中新的运动区域和提取人脸轮廓。

These changes not only appear in computer, detector and X ray technology but also in image reconstruction algorithm.

这些变化不仅体现在计算机技术、探测器技术和X线技术方面，同时CT的图像重建算法也在不断地发展。

Since historical times,England ,where the early inhabitants were Celts, has been conquered three times .

从有历史以来，英国，在此地早期居住的是凯尔特人，已经被征服了三次。

Bluetooth OBEX File Transfer Enables the sending and receiving of files on your phone via Bluetooth.

蓝牙OBEX文件移动允许经过蓝牙传送和接受文件。。。。