Description: 利用矩特征可以从二维图像识别三维目标,4阶矩的图像峰值反映了目标的形状,为了使它具有平移、比例和旋转不变性,作者对其进行了归一化处理。-use Moments from the three-dimensional two-dimensional image recognition, four bands peak moments of images reflect the shape of the target, In order to give it scale, translation and rotation invariant, the author of its normalized treatment. Platform: |
Size: 142336 |
Author:王城 |
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Description: hanks for downloading this code. This VB Project shows you how to make forms with "rounded rectangle" shape. It also shows you how you can reduce the size of your programs with a GUI by using blocks of images and absolutely positioning and stretching them to create a dialog box, rather than making the whole dialog box in a graphics program and setting it as the Picture property of the Form. Another advantage of using image blocks is that you can resize this form to virtually any size and the effect will still be the same. Platform: |
Size: 7168 |
Author:hbhuia |
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Description: The goals of this tool is to manipulate the fast marching algorithm in 2D and 3D. Application to shortest path extraction (e.g. road tracking and tubular structure extraction in medical images), shape statistics and geodesic remeshing are presented.-The goals of this tool is to manipulate the fast marching algorithm in 2D and 3D. Application to shortest path extraction (eg road tracking and tubular structure extraction in medical images), shape statistics and geodesic remeshing are presented. Platform: |
Size: 1349632 |
Author:费仙凤 |
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Description: 利用傅里叶描述子进行物体形状分析：
对于一个物体的边缘即形状来说，可将其看作是平面在空间坐标系下的点集构成的闭合曲线，这样就可用周期函数来描述其外形，可以进行离散傅里叶变换，将图像由空域表示转换到频域表示，变换后的函数可由傅里叶变换系数来描述。对于数字图像的频谱来说，低频分量的分布反映了图像主体的基本形状，高频分量的分布反映图像的细节-Fourier descriptors for object shape analysis: For the edge of an object or shape, it can be regarded as the plane in the space coordinates of the point set consisting of closed curves, so that periodic function can be used to describe its shape , can be discrete Fourier transform, the image from the airspace, said the conversion to the frequency domain that function can be transformed to describe the Fourier transform coefficients. For digital images of the spectrum, the distribution of low-frequency components reflect the basic shape of the main images, high-frequency component of the distribution reflects the image details Platform: |
Size: 11264 |
Author:吴亚鹏 |
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Description: 图像识别，通过矩阵计算分别读入图像的形状，可区分三角，椭圆，圆形，长方等规则几何-Image recognition, through the matrix, respectively, read into the shape of images, can be distinguished triangle, oval, round, rectangular, such as the rules of geometry Platform: |
Size: 36864 |
Author:徐宁 |
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Description: gabor_function1该程序对Gabor核函数某个尺度和方位的三维形状和二维平面图像进行显示
gabor_function2该程序对Gabor核函数五个尺度和八个方位的二维平面图像进行显示，共产生40个二维平面图像
这两个程序对理解gabor小波很有帮助哦-gabor_function1 the program of Gabor kernel function of a scale and orientation of the three-dimensional shape and two-dimensional images show that the program gabor_function2 of Gabor kernel five scales and eight-directional two-dimensional images show that a total of 40 have a two-dimensional Planar images of these two procedures useful in understanding the gabor wavelet Oh Platform: |
Size: 1024 |
Author:吴海峰 |
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Description: Recovering 3-D structure from motion in noisy 2-D images is a problem addressed by many vision system researchers. By consistently tracking feature points of interest across multiple images using a methodology first described by Lucas-Kanade, a 3-D shape of the scene can be reconstructed using these features points using the factorization method developed by Tomasi-Kanade. Platform: |
Size: 4657152 |
Author:Stephen Bishop |
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Description: 对形图像的经过边缘提取后得到的二值图像边缘进行细化，提取单像素的边缘，使得边缘是成为清楚的单像素的边缘。-After images of the shape after the edge extraction of the binary image to refine the edge, the edge extraction of a single pixel, making the edge is to be clear of the edge of a single pixel. Platform: |
Size: 2048 |
Author:mayan |
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Description: 本实验要求根据课本中给出的高斯噪声和椒盐噪声的概率分布的形状和参数编写两个通用程序分别给一个图像中添加高斯噪声和椒盐噪声。高斯噪声是n维分布都服从高斯分布的噪声，椒盐噪声是图像中经常见到的一种噪声是一种随机的黑点或者白点。在实验中通过它们对应的概率密度函数得到噪声分布函数进而与原图像进行叠加产生出对应的噪声图像-Textbooks in this experiment are given under the Gaussian noise and salt and pepper noise in the shape of the probability distribution and parameters of common procedures for the preparation of the two images were added to a Gaussian noise and salt and pepper noise. Gaussian noise is subject to the distribution of n-dimensional Gaussian noise, salt and pepper noise is often the image to see a noise is a random white spots or black spots. In the experiment through their corresponding probability density function of the noise distribution function to be the original image superimposed with the corresponding noise generated image Platform: |
Size: 243712 |
Author:jhm |
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Description: Lip image analysis has attracted much interest in
recent years because some important speech information is
contained in the shape and movement of the lip. To extract
such information from the lip images, accurate and robust
lip region segmentation is of vital importance. However,
most of the current lip segmentation methods fail to provide
accurate results if the person has beards. Platform: |
Size: 93184 |
Author:vikas |
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Description: ASM是由Cootes和泰勒推出的多分辨率方法的一个例子。
基本思想：
在ASM模型训练，训练从手工绘制的图像轮廓。发现的ASM模型在训练使用主成分分析（PCA），使该模型自动识别数据的主要变化是，如果可能的轮廓/好的对象的轮廓。还包含了ASM模型的协方差矩阵描述行垂直纹理口岸时，在正确的位置。
-Description This is an example of the basic Active Shape Model (ASM) as introduced by Cootes and Taylor, with multi-resolution approach.
Basic idea:
The ASM model is trained from manually drawn contours in training images. The ASM model finds the main variations in the training data using Principal Component Analysis (PCA), which enables the model to automatically recognize if a contour is a possible/good object contour. Also the ASM models contains covariance matrices describing the texture of the lines perpendicular to the control points when in the correct positions.
After creating the ASM model, an initial contour is deformed by finding the best texture match for the control points. This is an iterative process, in which the movement of the control points is limited by what the ASM model recognizes from the training data as a "normal" object contour.
Literature:
- Ginneken B. et al. "Active Shape Model Segmentation with Optimal Features", IEEE Transactions on Medical I Platform: |
Size: 10190848 |
Author:谢冉 |
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Description: 此压缩文件中包含了半学期以来做的所有的计算机图形学实验，包括DDA生成直线和圆，扫面线填充任意形状的图形的算法、运动的小车、月绕太阳转、抛物线的生成、星形的生成、点阵式、矢量式算法实现的字符的生成，二维图形的各种变化用矩阵的方法实现，三维图形的投影等，实验内容丰富全面，而且都能在TC下运行，生成显示图像。-This compressed file contains a half-term has to do all the computer graphics experiments, including the DDA to create line and circle, scanning line filling algorithm for arbitrary graphical shape, sports car, dated around the sun, the formation of a parabola, star shape generation, dot matrix, vector-type algorithm for character generation, two-dimensional graph of the changes achieved with the matrix method, three-dimensional graphics projection, a comprehensive experimental content-rich, and can run in the TC to generate display images. Platform: |
Size: 140288 |
Author:孟萌 |
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Description: Gabor滤波器经常被用于形状检测和特征提取，比如增强指纹图像。本代码用matlab实现了一个二维Gabor滤波器。
代码使用如下：
function [G,gabout] = gaborfilter1(I,Sx,Sy,f,theta)
from gaborfilter1 with different f(Frequency) and theta(Angle).
for example
f:0,2,4,8,16,32
theta = 0,pi/3,pi/6,pi/2,3pi/4
then for any input image like(eg. stereo.jpg)
you have 6x5 = 30 filtered images.
You can choose your desired angles or frequencies.
You can put nominaly Sx & Sy = 2,4 or some one else.
For instance I tested above example on ( cameraman.tif )(in MATLAB pictures)
I = imread( cameraman.tif )
[G,gabout] = gaborfilter1(I,2,4,16,pi/3)
figure,imshow(uint8(gabout)) -Gabor filters are often used for shape detection and feature extraction, such as the enhanced fingerprint image. Matlab implementation of the code is a two-dimensional Gabor filter. Use the following code: function [G, gabout] = gaborfilter1 (I, Sx, Sy, f, theta) from ' gaborfilter1' with different f (Frequency) and theta (Angle). For example f: 0,2,4, 8,16,32 theta = 0, pi/3, pi/6, pi/2,3 pi/4 then for any input image like (eg. stereo.jpg) you have 6x5 = 30 filtered images. You can choose your desired angles or frequencies. You can put nominaly Sx & Sy = 2,4 or some one else. For instance I tested above example on (' cameraman.tif' ) (in MATLAB pictures) I = imread (' cameraman.tif' ) [G, gabout] = gaborfilter1 (I, 2,4,16, pi/3) figure, imshow (uint8 (gabout)) Platform: |
Size: 1024 |
Author:郑碧波 |
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Description: 实现图像的清晰分割，效果明显,基于图像灰度-梯度构造的二维直方图，在此基础上计算目标与背景的二维Renyi熵-It can handle more types of images and get more accurate shape of the image edgee that pixels gradient information in combination with parameter of Renyi entropy which is adjustable Platform: |
Size: 9216 |
Author:jin |
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Description: CBIR is retrieval of images based on some query or example images. It is also called Query based image retrieval. Firstly, this report outlines a description of the primitive features of an image color and shape. These features are extracted and used as the basis for a similarity check between images. The final result is a MatLab built software application, with an image database, that utilized color and shape features of the images in the database as the basis of comparison and retrieval. Platform: |
Size: 304128 |
Author:keerthi |
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Description: 数字图像处理matlab实现，包括如下程序：
1.直方图规定化为高斯双峰函数
2.窗口形状自适应（十字形或矩形）的中值滤波
3.彩色图像目标提取并与背景图像合成
4.插值外推法的彩色图像饱和度调整
5.多种插值方法实现的图像放大和缩小
6.频域变换及分析
7.几何校正
8.插值外推法的黑白图像对比度增强
9.运动模糊矫正-Digital image processing matlab realize, including the following procedures: (1) the bimodal histogram specification as a function of two Gaussian shape adaptive window (cross or rectangular) median filtering three color image with the background object extraction and image synthesis 4. Color image interpolation extrapolation saturation adjustment 5. various interpolation methods to achieve images zoom in and out 6. frequency domain transformation and analysis 7. geometric correction 8. interpolation extrapolation of the black and white image contrast enhancement 9. motion blur correction Platform: |
Size: 7168 |
Author:Yan |
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Search - shape in images matlab