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dual graph相关的网络例句

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This paper defines j-dual automorphism and anti- automorphism of de Bruijn Good graph Gn over F2+vF2 ring.

文章定义了F2+vF2环上的de Bruijn Good图Gn的j对偶自同构及反自同构,并给出了在F2+vF2环上移位寄存器非奇异的充要条件,以及非奇异反馈函数与其自同构函数的表达式。

The study includes the fuzzy independent set, fuzzy bases, fuzzy circuits, fuzzy rank, fuzzy hyperplanes, fuzzy closure operator, fuzzy submatroid, quasi-fuzzy graph matroids, fuzzy graphic matroids, fuzzy dual matroid and so on.

研究的内容包括模糊拟阵的独立集,模糊基,模糊圈,模糊秩函数,模糊超平面,模糊闭包算子,模糊子拟阵,准模糊图拟阵,模糊图拟阵,模糊拟阵的对偶和模糊拟阵的运算等等。

The study includes fuzzy bases, fuzzy circuits, fuzzy rank function, fuzzy hyperplanes, fuzzy closure operator, fuzzy submatrods, quasi-fuzzy graph matroid, fuzzy graphic matroids, fuzzy dual matroid and so on.

研究的内容包括模糊拟阵的模糊基,模糊圈,模糊秩函数,模糊超平面,模糊闭包算子,模糊子拟阵,准模糊图拟阵,模糊图拟阵,模糊拟阵的对偶等等。

According to the Marr's visual theory, a novel face image presentation model, dual attribute graph , is put forward in the thesis. Each node of the graph has two attributes, local principal component coefficient and Gabor coefficient. So the presentation of face image can be converted from gray level to more high level.

根据Marr的视觉表示理论,本文提出了新的人脸图象表示形式---双属性图表示,属性图中每个节点有两个属性特征,局部主成分系数特征以及Gabor系数特征;从而将人脸图象的灰度级表示,转化为更高一级表示。

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。

A new method for understanding the construction of dual links has been developed on the basis of medial graph in graph theory and tangle in knot theory.

基于图论中反转中间图的方法和纽结理论中的缠绕理论,我们提出了构建对偶链环的新方法。

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