文件名称:Gabor_GLM_FEX
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2017-05-11
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- 3kb
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视网膜血管检测的Gabor变换和机器学习，教程
本教程将演示如何Gabor变换和广义
的线性模型（GLM）可用于视网膜血管检测
图像。
，我们将尝试检测视网膜血管从
的训练图像，首先，Gabor滤波器与图像卷积。
GLM将使用Gabor变换的图像特征确定
（独立变量）和容器的位置
为结果（因变量）。- Retinal Vessel Detection by Gabor Transform and Machine Learning, a Tutorial
This tutorial will demonstrate how Gabor transforms and generalized
linear model (GLM) can be used for detection of retinal vessels in
images.
Specifically, we will attempt to detect the retinal vessels a
training image , by first, convoluting multiple Gabor filters with the image.
A GLM will be determined using the Gabor transformed images as features
(the independent variables), and the locations of the vessels
as the outcome (the dependent variable).
本教程将演示如何Gabor变换和广义
的线性模型（GLM）可用于视网膜血管检测
图像。
，我们将尝试检测视网膜血管从
的训练图像，首先，Gabor滤波器与图像卷积。
GLM将使用Gabor变换的图像特征确定
（独立变量）和容器的位置
为结果（因变量）。- Retinal Vessel Detection by Gabor Transform and Machine Learning, a Tutorial
This tutorial will demonstrate how Gabor transforms and generalized
linear model (GLM) can be used for detection of retinal vessels in
images.
Specifically, we will attempt to detect the retinal vessels a
training image , by first, convoluting multiple Gabor filters with the image.
A GLM will be determined using the Gabor transformed images as features
(the independent variables), and the locations of the vessels
as the outcome (the dependent variable).
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Gabor_GLM_FEX.m