image map

image map的基本解释

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图象映射

与image map相关的网络例句 [注：此内容来源于网络，仅供参考]

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。

This article detailedly expatiated upon the principles, contents and methods of cropland classification; it analyzed the necessity to combine the work of cropland classification with GIS technology, summarized the attributions of ARC/INFOand some other related softwares; it established the technologic route of cropland classification supported by GIS, by a case study in Liwu Town,Li County Hebei Province, this article expatiated the practicable mechanism of combining the function of ARC/INFO with the work of cropland classification, and put forward some new ideas and approaches of utilizing GIS: this paper put forward the idea of coding the polygons in the basic graphic database such as soil map and land use map according to their attributes, and put forward the detailed coding project; based on the code databases, it expatiated upon the detailed approaches to create single梖actor map and output the final classification map; it put forward the principles and the method of creating classification units in the environment of GIS, that is how to keep the lines of soil polygon, the border of districts and the important objects such as residential areas, banks of rivers and roads ,and how to overlap single梖actor soil map and land use map, and to delete some vector lines of the overlapped map appropriately; it detailed the methods of creating mathematic model of classification coefficients in the environment of computer, and used FOXPRO6.0 programs to realize the automation of calculating coefficients; it represented the method of plotting the final map by overlapping various coverages according to the code tables and lookup tables, the process of outputting the cropland classifying map was finished by program.

本文法对耕地等别划分的原则、内容及方法作了较详细的阐述，介绍了多系数综合修正法的耕地等别计算方法及其具体应用和AHP的确权方法；分析了耕地等别划分工作与地理信息系统技术相结合的必要性，简要介绍了地理信息系统软件ARC／INFO及其他相关软件的功能特点，制定了地理信息系统支持下耕地等别划分的技术路线，通过对河北省蠡县蠡吾镇的实证研究，重点阐述了ARC／INFO及相关数据库软件与耕地等别划分结合的有效机制及GIS应用的一些新思想、新方法：提山了对土壤图和土地利用现状图等基础图形数据库进行特征编码的思想和具体的编码方案，阐述了基于与图形库相链接的特征编码表，单因素图提取、成果图的输出的具体实现方法；提出了GIS环境下耕地单元划分的原则和方法，即在保留土壤因素图斑界线、行政界线和重要地物等的原则下，将土壤单因素图和土地利用现状图进行拓扑叠加，对叠加图中的矢量线进行适当的删除；阐述了在计算机环境下，耕地分等参数计算模型建立的方法，并用FOXPRO6.0语言程序实现了参数计算的自动化；阐述了根据图形库特征编码表和建立绘图符号查找表，按不同图层叠加绘制成果图的方法，该过程用命令程序实现耕地等别图的输出。

To increase the security of the watermark, a new binary image encryption algorithm based on TD-ERCS map is presented. The watermark is encrypted by a chaos sequence generated by TD-ERCS map; A novel color image watermarking algorithm is proposed based on discrete chaotic map and 2-dimensions discrete wavelet transform. The watermark is encrypted by the new binary image encryption algorithm, and the encrypted watermark is embed into four sub-bands of the most deep level of blue branch of host image by three-level wavelet transform, and the embedded positions are determined by general cat cha otic map; A novel color-image blind detection watermarking algorithm is proposed based on integer wavelet transform and subsampling. The scrambled watermark is encrypted and embed into the low sub-bands after four sub-images of the Y branch of host image is transformed by two-level wavelet transform, and the embedded positions are determined by Logistic chaotic map, this watermarking scheme can realize blind extraction.

为了提高水印图像的安全性，提出了一种基于TD-ERCS混沌映射的二值水印图像的加密算法，该算法利用TD-ERCS映射产生的混沌序列加密水印图像；将离散混沌映射和二维离散小波变换相结合，研究了彩色图像水印新算法，该算法先对混沌序列加密后的水印图像进行小波变换，再嵌入到宿主图像的蓝色分量的最深层的四个子带中，嵌入位置则由广义猫映射确定；将整数小波变换和图像子采样技术应用于数字水印，提出了一种彩色图像盲提取水印算法，水印嵌入时，先对宿主图像在YIQ色彩空间中的Y分量进行子采样，并对得到的四个子图像分别进行二级离散小波变换，然后将置乱并加密后的水印图像嵌入到小波变换后的低频子带中，其嵌入位置由Logistic混沌映射产生的混沌序列确定，实现了水印的盲提取。

与image map相关的网络解释 [注：此内容来源于网络，仅供参考]

Image map：影像地图

要完成地图区域超链接要用到三种标签:下面分别介绍这些标签的用法: 影像地图(Image Map)标签的使用格式:

Image map：图像映射图

Lesson 12 添加样式预设模块集合(Presets Library)第3阶段 设置各个图像区域的GIF、JPG、PNG格式(Optimize)第4阶段 Rollover图像操作(Rollover),GIF动画文件(Animation),使用图像映射图(Image Map),设置文件名、链接以及区分文本区

Image map：影像对应

提供安全色盘的使用和转换,要切割图形,做影像对应(Image Map)景透明,要图又小又漂亮,在 Fireworks 4 中做起来都非常方便,修改图形也是很容易的.不需要再同时打开Photoshop 和 CorelDRAW...等等各类软体切换来切换去的了.

Image map：图像地图

选择和重命名网页对象.网页设计师在网页中应用热区和图像地图,可以使页面的浏览更加的简捷.热区(hotspot)也就是在网页上图像对应的某一个区域添加 URL(全球资源定位) 链接.图像地图(image map)也就是在网页中的某一幅图像上应用多个热区,

photomap, image map：影象地图

image geometry 图象几何测定 | photomap, image map 影象地图 | digital code 数字编码