搜索资源列表
BayesianClassificationAlgorithms
- 本程序是实现两类正态分布模式的贝叶斯分类，简单易懂-The program is to achieve the two types of normal distribution model Bayesian classifier, straightforward
DlgZhiFangTu
- 画图像的灰度直方图，对图像的分析有很好的帮助，由直方图的分布选择合适的图像处理方法。-Videos image histogram analysis of the image has a good help select the appropriate image processing method, by the distribution of the histogram.
Test_edge
- 统计车牌图像的边缘规律，叠加多幅图像给出一般的车牌分布规则-The edge of the law of statistics license plate image superimposed multiple images to give a general license plate distribution rules
linear
- 图像的线性变换，包括图像的亮度，对比度以及直方图分布。-The linear transformation of the image, including the brightness of the image, contrast, and histogram distribution.
HS
- 這種方法通常用來增加許多圖像的全局對比度，尤其是當圖像的有用數據的對比度相當接近的時候。通過這種方法，亮度可以更好地在直方圖上分布。這樣就可以用於增強局部的對比度而不影響整體的對比度，直方圖均衡化通過有效地擴展常用的亮度來實現這種功能。 -This method is usually used to increase the global contrast of many images, especially when the useful data of the image contras
GaossT.m
- 正态分布二维矩阵的生成。sum=0。高斯二位矩阵-Normal distribution the generation of two-dimensional matrix. sum = 0. The gauss two matrix
blue
- 一辆车的图片中蓝色车牌的检测，根据像素的分布实现初步定位，检测结果比真实区域只大不小-Blue picture of a car license plate detection based on the pixel distribution to achieve the initial positioning, test results than the real area only large and small
OpenCV_HistSpecification
- 数字图像处理 直方图规定化 将原图的灰度直方图按照目标图像的灰度直方图分布进行变换，得到符合目标灰度分布的直方图-Digital Image Processing Original gray histogram provides distribution histogram of the target image gray histogram transform to meet the target gray histograms
junheng
- 用直方图均衡化对图像进行处理。直方图均衡化主要用于增强动态范围偏小的图像的反差。该方法的基本思想是把原始的直方图变换为均匀分布的形状，这样就增加了像素灰度值的动态范围，从而达到增强图像整体对比度的效果。-Histogram equalization on the image processing. Histogram equalization is used to enhance the contrast of the image dynamic range is small. The basi
pupil-localization
- 本函数选用阈值分割的方法来完成瞳孔定位。根据图像的灰度分布特性，瞳孔部分的灰度值最小，其次为虹膜部分，最大的为巩膜部分。因此在灰度直方图中，第一个大峰值的邻域即是瞳孔所在区域。-Function selects the threshold segmentation method to accomplish the pupil location. Based on image gray distribution features, the pupil part of the grey valu
Problem1
- 这个程序可以用于描述钟摆的摇摆轨迹的分布-This program can be used to describe the distribution of the trajectory of the pendulum swing
2
- 实现图像处理中，实现对一幅灰度图像的快速傅立叶变换,并求其变换后的系数（幅度）分布，同时实现对一幅图像做离散余弦变换,选择适当的DCT系数阈值对其进行DCT反变换 -Realize image processing, to achieve the fast Fourier transformation of a grayscale image, and determine the distribution of its transform coefficients (amplitude), wh
locatepoint3
- 手工定位人脸图像上5个特征点，分布是左右眼、鼻尖、鼻子边缘切线点、下巴-Manually positioned face image on the five feature points, the distribution is the left and right eyes, the nose, the nose edge tangent point, chin
DFF-program
- 分布傅里叶变化在非线性光学与数字图像处理中有广泛的应用-Changes in the distribution of Fourier a wide range of applications in nonlinear optical and digital image processing
Image-Signal-processing
- RGB to HSI Conversion:A color histogram is a representation of the distribution of colors in an image. The method is useful in images with backgrounds and foregrounds that are both bright or both dark.
3
- 迭代法 迭代式阈值选取的基本思路是:首先根据图像中物体的灰度分布情况， 选取一个近似阈值作为初始阈值-Iterative threshold selected basic idea is: First, the gray-scale distribution of objects in the image, select an approximate threshold as initial threshold
DCT-change
- 1.实现对lena.bmp灰度图像的快速傅立叶变换,并求其变换后的系数（幅度）分布； 2.实现对lena.bmp图像做离散余弦变换,选择适当的DCT系数阈值对其进行DCT反变换 ；-1 to achieve the fast Fourier transform on lena.bmp grayscale image, and to find the transformed coefficients (amplitude) distribution 2. To achieve lena.bm
zhifangtupipei
- 把原图像的直方图按照给定的直方图加以映射，使新图像的直方图的分布类似于给定的函数。 总共有以下几步： 1.求给定的函数的累积直方图s。 2.求原图像的累积直方图G。 3.求s中每一个值在G中距离最小的位置index。 4.求原图像每个像素通过index映射到的新像素的值。-The histogram of the original image to be mapped, in accordance with the histogr
fractal-box
- 用差分盒维数处理图像，通过对图像分块，然后每一块来计算该区域的分维数，将其作为该区域所有像素上每一像素的分维数。然后，增强分维数分布图效果，然后取阈值，最后，给人造目标加框。-Differential box counting process the image, the image block, and then every one to calculate the fractal dimension of the region, as all the pixels in the region
levelset
- 基于边界和G0分布的水平集迭代图像分割算法-level set segmentation based on edge and g0 distribution