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visual image相关的网络例句

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It solves the problem that the unitary contour presentation can not correctly extract face contour in a face image which suffers from scale, rotation etc. The definition of the internal and external energy function is provided. At the same time, the global matching algorithm and local matching algorithm is given. The experiment shows that this presentation and the accompanying matching algorithm can be used to extract the face contour very well. So the image segmentation can be implemented by using it.②By analyzing the recognition principle of PCA method, we can conclude that the face images coming from different surrounding consist of different face image space. This is the essential reason that makes the generality of PCA method worse. Also, we give a measurement means to measure the distance from different face image space, so we can analyze face image space more conveniently.③We also construct various scale models and rotation pose models to detect the scale and rotating angle of face image to be recognized. The experiment results show that the detecting precision is very high. So it is good for face image feature extraction and face image representation.④Similarly, we construct local feature models of face image and utilize them to detect the local feature of face image. At the same time, we put forward a novel face image local feature detection algorithm, locating step by step. The experiment results show that this method can accurately detect the location of local face feature in a image.⑤A novel face image presentation model, dual attribute graph , is put forward. Firstly, it utilizes attribute graph to present the face image, then exact the local principal component coefficient and Gabor transform coefficient of thc pixels which corresponds to the nodes of the graph as the attribute of the nodes. This representation fully makes use of the statistical characteristic of the local face feature and utilizes Gabor transform to present the topographical structure of face image. So DAG has more general property.⑥Based on the DAG presentation, we give a DAG matching function and matching algorithm. During the design of the function and algorithm, the noise factor, e. g., lighting, scale and rotation pose are considered and tried to be eliminated. So the algorithm can give more general property.⑦A general face image recognition system is implemented. The experiment show the system can get better recognition performance under the noise surrounding of lighting, scale and rotation pose.

本文在上述研究的基础上,取得了如下主要研究成果:①构造了一个通用的人脸轮廓模型表示,解决了由于人脸图象尺度、旋转等因素而使得仅用单一轮廓表示无法正确提取人脸轮廓的问题,并给出了模型内、外能函数的定义,同时给出了模型的全局与局部匹配算法,实验表明,使用这种表示形式以及匹配算法,能够较好地提取人脸图象的轮廓,可实际用于人脸图象的分割;②深入分析了PCA方法的识别机制,得出不同成象条件下的人脸图象构成不同的人脸图象空间的结论,同时指出这也是造成PCA方法通用性较差的本质原因,并给出了不同人脸空间距离的一种度量方法,使用该度量方法能够直观地对人脸图象空间进行分析;③构造了各种尺度模板、旋转姿势模板以用于探测待识人脸图象的尺度、旋转角度,实验结果表明,探测精确度很高,从而有利于人脸图象特征提取,以及图象的有效表示;④构造了人脸图象的各局部特征模板,用于人脸图象局部特征的探测;同时提出了一种新的人脸图象局部特征探测法---逐步求精定位法,实验结果表明,使用这种方法能够精确地得到人脸图象各局部特征的位置;⑤提出了一种新的人脸图象表示法---双属性图表示法;利用属性图来表示人脸图象,并提取图节点对应图象位置的局部主成分特征系数以及Gabor变换系数作为图节点的属性,这种表示方法充分利用了人脸图象的局部特征的统计特性,并且使用Gabor变换来反映人脸图象的拓扑结构,从而使得双属性图表示法具有较强的通用性;⑥在双属性图表示的基础上,给出双属性图匹配函数及匹配算法,在函数及算法设计过程中,考虑并解决了光照、尺度、旋转姿势变化等因素对人脸图象识别的影响,使得匹配算法具有较强的通用性;⑦设计并实现了一个通用的人脸图象识别系统,实验结果表明,该系统在图象光照、尺度、旋转姿势情况下,得到了较好的识别效果。

It includes hardware equipments and foundational theory of the image digitization. This paper expatiates on some digital image processing technologies that the inspecting system may apply to the research and analysis of the collected glass-crack image. Using neighborhood average method and median filter retrains the image noises and make the image edge smooth. Then protract the histogram of the gray image, get the threshold of this image, utilize the threshold method and gray-level slice method to get a binary image, and detect the image edge. Finally calculate the area and perimeter of the glass-crack image, and use the circularity to judge whether this image is a glass-crack image.

本文重点阐述了研究和开发这套玻璃瓶裂纹检测系统所应用到的一些数字图像处理技术,并应用这些技术和方法对采集的裂纹图像进行了处理和分析:应用邻域平均法和中值滤波法来抑制图像的噪声,使图像的边缘平滑;然后绘制出处理过图像的灰度直方图,得到该幅裂纹图像的阈值,利用阈值法和灰度级切片法对裂纹图像进行二值化处理,得到其二值图像,并对图像进行了边缘检测;最后计算出裂纹图像的面积和周长,利用圆形度指标来判断该图像是否为裂纹图像。

An image formation apparatus comprises: an image formation apparatus main body; plural image formation units being provided detachably in the image formation apparatus main body, each of the image formation units including an image carrier and an exposure device that applies light to the image carrier for writing a latent image onto the image carrier; and a positioning section that positions the exposure device of each of the image formation units relative to the image formation apparatus main body.

本发明公开了一种图像形成装置,包括:图像形成装置主体;多个图像形成单元,其可拆卸地设在所述图像形成装置主体中,每个所述图像形成单元包括图像载体和曝光装置,所述曝光装置向所述图像载体照射光,以将潜像写入到所述图像载体上;以及定位部分,其相对于所述图像形成装置主体定位各个所述图像形成单元的曝光装置。

The invention discloses the anti-fake method by using the 3D stereoscopic icon, which can show 3D stereoscopic icons and hide the confidential image information in the 3D stereoscopic icons, comprising the following steps of: obtaining parameters, inputting confidential images and grey images; then using a visual divided storage method to build n visual divided storage images, using a 3D stereograph method to build n 3D stereoscopic images, adjusting the sizes of the n visual divided storage images and the n 3D stereoscopic images and dividing the n visual divided storage images and the n 3D stereoscopic images into a plurality of basic blocks; finally random choosing the basic blocks in the corresponding positions in the visual divided storage images or the 3D stereoscopic images to build n 3D stereoscopic and visual divided storage icons, etc.

为了既能三维立体显示图标,又能在三维显示的图标中隐藏秘密图像信息,本发明公开了利用三维立体图标防伪的方法,包括获取参数,输入秘密图像和灰度图像;然后利用可视分存方法构造n幅可视分存图,利用三维立体画方法构造n幅三维立体图,调整所述n幅可视分存图和所述n幅三维立体图大小并分成多个基本块;最后随机选取可视分存图或三维立体图中相应位置处的基本块,构造n幅三维立体可视分存图标等步骤。

The main outcome measures were uncorrected distant visual acuity , best corrected distant visual acuity , uncorrected near visual acuity , distant-corrected near visual acuity , the best corrected near visual acuity , defocus curves and depth of focus, the rate of posterior capsule opacification of the study group, IOL decentration distance of the study group. A questionnaire was applied to evaluate the visual function and rate of spectacles usage.

术后检查内容包括:术后裸眼远视力、最佳矫正远视力、裸眼近视力、矫正远视力时的近视力、最佳矫正近视力;在两组患眼中选择最佳矫正远视力≥0.9的患眼进行焦点深度及离焦曲线测量;观察实验组后囊膜混浊情况;选取实验组的部分病例进行散瞳裂隙灯照相测量人工晶状体偏中心的距离。

Retinotopy; color sensitivity; color-selective region; lateral geniculate nucleus; visual cortex; area V8; area V1; cones; visual pigments; fovea centralis; macula lutea; red; green; blue; Young-Helmholtz theory; short-wavelength-sensitive cones; medium-wavelength-sensitive cones; long-wavelength-sensitive cones; S cones; M cones; L cones; visual perception; ectostriatum; tectofugal visual pathways; thalamofugal visual pathways; color-reversal learning; visual Wulst

retinotopy;感色灵敏度;颜色-选择区;侧膝体核;直观皮层;区域V8;区域V1;圆锥细胞;视色素中央凹;黄斑;红色;绿色;蓝色;三原色学说;短波长敏感圆锥细胞;中波长敏感圆锥细胞;长波长敏感圆锥细胞;S圆锥细胞;M圆锥细胞;L圆锥细胞;视觉;ectostriatum;tectofugal视路;thalamofugal视路;颜色-倒序学习;visual Wulst

By means of equalizing the histogram, the contrast of original thermal image is enhanced; then image region of the disc surface of insulator is intercepted manually; through the envelope of the smoothened histogram of thermal image the segmentation threshold is extracted and the morphological filtering is applied to the threshold- segmented binarized image to obtain insulator disc surface image and background image, and then 10 infrared image features of insulator disc surface image and background image, such as the highest temperature, the lowest temperature, mean temperature, variance of temperature distribution of both kinds of images, as well as maximum temperature rise and mean temperature rise of insulator disc surface relative to background, are extracted; finally, the good and bad features are discriminated by single factor variance analysis, thus the feature selection is implemented.

利用直方图均衡化增强原始热像图对比度,人工截取绝缘子盘面图像区域;通过平滑后的图像直方图包络线提取分割阈值,对阈值分割后的二值图像进行形态学滤波,得到绝缘子盘面图像和背景图像,提取2者的最高温度、最低温度、平均温度、温度分布方差以及盘面相对于背景的最大温升和平均温升共10个红外热像特征;应用单因素方差分析甄别特征优劣,实现特征选择。

The design , which is based on the realization of dot operation of Visual C# digital image processing, exterts the object-oriented design technology and the technology on digital image processing, taking visual c#.net as a tool of system utility program development, and microsoft visual studio.net as integrated development enviornment, to develop system software by utility programming and GDI+,and to supports eight functions of digital image processing: inversecolour processing,graylevel processing ,brightening processing,embossment processing,edge test ,image smoothing, darkening processing and transparent processing.

用Visual C#。net 进行数字图像处理是我的一个全新的尝试,它具有开发过程简明,开发方式灵活,扩展性强等特点,是一种被广泛运用的前端开发平台。Visual C#。net提供多种多样的编程技术,对于一个刚入门不久的新手来说无疑是个挑战,尤其是图像处理中的算法,是个大难题,该问题也是这次毕业设计所要解决的主要问题,不过我想能够有毕业设计这个难得的机会使我对VC#有了一个更深入的了解。态度决定一切,只要你认真对待了,就一定会有收获。注:此文版权归本站所有,需付费购买,本站保证购买者的省唯一性。

In such doing, this dissertation serves as a step stone for papers of its counterparts to come, and, more importantly, it proposes a strategic alternative to the realization of models for image processing. This dissertation consists of three major parts. In the first part, detailed discussions and delicate analyses of academic papers on Cellular Neural Network will be provided in the hope of helping us see the potentiality of Cellular Neural Network in the applications of image processing. I will focus on the aforementioned limitations on hardware compilation as well. In the second part, I will put forth "texture analysis" as one basic model of analysis when we apply Cellular Neural Network to image processing. In this so-called texture analysis, a useful "spatial feature" is especially drawn to help us overcome possible problems of more complicated Cellular Neural Network applications in image processing."Spatial feature" also serves as a well-functioning mechanism for technology of image identification. In the last part of this thesis, I will look into a case study, where Cellular Neural Network is applied to help de-screen document image. Using it as an example, we will see how algorithms of Cellular Neural Network may be of marvelous use in applications in document image processing, since it would reduce a great deal of calculation and computation when applied to software compilation, yet opens up unlimited possibilities for higher-speed hardware compilation of high-level image processing.

这篇论文主要可以分为三大部分:在第一部份里,我们会详细地说明并讨论在过去到现在大部分将分子类神经网路应用於影像处理的相关文献及未来所有可能的发展和技术,另外也将分子类神经网路作一完整的介绍,除此之外,我们也会特别著重於分子类神经网路在影像处理相关应用理论的讨论以及其硬体实现化的考量;在第二部分里,我们提出了一个将分子类神经网路应用於影像辨识处理的基础分析—纹路分析,这是由於纹路分析的复杂性和普遍性会使得分子类神经网路於高阶影像处理的应用不会只局限在单一的影像处理技术,其中我们也提出了一个相当有用的空间特徵,此一特徵不但可以使复杂地高阶影像处理能够应用分子类神经网路,也为影像辨识技术提供了一个很好的辨识机制;在最后一部分里,我们也将文件影像分析做了一个完整的剖析,并以文件影像的去网点为例来说明在实际情况下的分子类神经网路的应用,如此演算法的开发也为文件影像处理提供了更多实际的应用,更考量了文件影像处理若以软体实现时的计算量负荷,而对未来高阶数位影像处理能够以硬体实现来提高处理速度提供了无限的可能。

A complete set of image processing and recognition of the source code This is our internal development and use of a image processing code, includes the most image processing and recognition processing function : as template transform, Image smoothing, sharpening, edge recognition, image filtering and fuzzy images, image inverse filtering, fuzzy image noise increases, Wiener filter images, linear transformation, gray tensile, histogram equalization, images corrosion, expansive images, image open operation, GIF correct coding, zooming, rotation, fast Fourier transform, discrete cosine transform, and so on and so forth, that is too many.

详细说明:一套完整的图像处理与识别的源码这是我们内部开发与使用的一套图像处理代码,里面包括了大部分图像处理与识别处理的的函数:像模板变换,图像的平滑、锐化、边缘识别、图像中值滤波、图像模糊、图像逆滤波、图像模糊加噪、图像维纳滤波、线性变换、灰度拉伸、直方图均衡、图像腐蚀、图像膨胀、图像开运算、GIF确码编码、缩放、旋转、快速付立叶变换、离散余弦变换等等,等等,太多了。

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相关中文对照歌词
In His Image
Visual Love
Think Visual
Shock Box
I Get Visual
Mirror Image
Sage Comme Une Image
Shattered Image
Image Of The Invisible
Imagine That
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