Description: 此设计要求能够实现将医学图像进行识别的过程，包括了图像预处理、图像特征提取及分类判决三大模块。在预处理这一步中主要实现的是将彩色图像转换为灰度图像，灰度图像的二值化，直方图修正，去除干扰、噪声以及差异，边缘增强等；第二模块是图像的特征提取。由于对象的物理与几何特性差异，在影像中表现为局部区域的灰度产生明显变化，形成影像特征，而图像特征提取就是对其进行加工、整理、分析、归纳以便提取构成目标影像的特征，得到能反映图像内容区别于其他事物的本质特征；分类判决作为第三模块，则是要在第二步的基础上采用某种分类判别函数与判别规则，通过对目标特征的分析和匹配来识别目标。-this design requirements to achieve medical image identification process, including the image preprocessing, Image feature extraction and classification ruling three modules. This pretreatment step in the main achievement of the color image is converted to grayscale images, the two gray-scale image value, histogram amendment to remove interference and noise variance Edge Enhancement; the second module is the image feature extraction. Because of the physical objects with geometric characteristics difference in the images showed local area Gray significant changes, the video features, feature extraction and image is its processing, compilation, analysis, summarized in order to extract constitute the target image features can be reflected image as distinct from the other characteristics of th Platform: |
Size: 6144 |
Author:uhih |
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Description: 人脸检测，基于gabor的提取特征，利用人工神经网络进行人脸检测-Face detection, based on the extraction of gabor features, the use of artificial neural networks Face Detection Platform: |
Size: 15401984 |
Author:smallbearpapa |
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Description: 能够提取出图像I的HOG特征，返回其幅值，角度和在各个角度上的幅值。
是进行其他针对图像的HOG特征提取的前一步。-I can extract images of HOG features, return to their amplitude, angle and perspective in all of the amplitude. Is the other for image feature extraction HOG step forward. Platform: |
Size: 1024 |
Author:郑帅 |
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Description: 纹理元抽取 并计算纹理元的特征 数学形态学实现 原理简单、适用性强-Texture element extraction and calculation of texture features yuan realize the principle of mathematical morphology is simple, applicability Platform: |
Size: 1024 |
Author:liyi |
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Description: 基于ORL人脸库的人脸识别的特征人脸的提取源代码。-Based on the ORL face database for face recognition facial features extraction source code. Platform: |
Size: 4096 |
Author:yuzhun21 |
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Description: Tamura纹理特征提取程序，matlab编写，通过运行测试无误。另附有pdf介绍Tamura纹理特征定义，希望对大家有帮助。-Tamura texture feature extraction procedures, matlab prepared correctly by running the test. Tamura has attached pdf introduce the definition of texture features, in the hope that everyone has to help. Platform: |
Size: 703488 |
Author:段西尧 |
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Description: 子模式主成分分析首先对原始图像分块，然后对相同位置的子图像分别建立子图像集，在每一个子图像集内使用PCA方法提取特征，建立子空间。对待识别图像，经相同分块后，分别将子图像向对应的子空间投影，提取特征。最后根据最近邻原则进行分类。-Sub-mode principal component analysis first of the original image block, and then the same sub-image, respectively, the location of the establishment of sub-image set, in each sub-image set to use PCA to extract the features, the establishment of sub-space. Treatment to identify images, by the same block, the respective sub-image to the corresponding sub-space projection, feature extraction. Finally, according to the principle of nearest neighbor classification. Platform: |
Size: 165888 |
Author:tanghui |
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Description: matlab编写的图像处理程序，用于提取图像的纹理、颜色特征。-matlab image processing procedures to prepare for the extraction of image texture and color features. Platform: |
Size: 2048 |
Author:杨 |
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Description: 图像特征识别通过神经网络训练方法实现，是学习参考的好资料-you will need first to run the file that name "charGUI4.fig" and on the right side there is a load training set where you have to train the system first, run any data that is should be from 1 to 9 and 0 like ( 1 2 3 4 5 5 6 7 8 9 0) as many line as you want so if you have a traning data that is 10 columns by 5 lines then you have to assign that to the small boxes that name column and line. right now keep the#words as is because I plan to use it but I change my mind so that it is automatically count the word for you.
after you train the system then load any image test, from the "Load Image" once you upload the image then choose the "select" and then go to the uploaded image and select whatever you want to recognize, after that select "crop" to crop the exact part that you want to recognize after that selcet "Features Extraction" to extract the features after that choose the "recognize" to see the results up on the result box.
P.S. keep in mind that the program has been tested on the Platform: |
Size: 709632 |
Author: 反对撒 |
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Description: Feature extraction is a key issue in contentbased
image retrieval (CBIR). In the past, a number of
texture features have been proposed in literature,
including statistic methods and spectral methods.
However, most of them are not able to accurately capture
the edge information which is the most important texture
feature in an image. Recent researches on multi-scale
analysis, especially the curvelet research, provide good
opportunity to extract more accurate texture feature for
image retrieval. Curvelet was originally proposed for
image denoising and has shown promising performance.
In this paper, a new image feature based on curvelet
transform has been proposed. We apply discrete curvelet
transform on texture images and compute the low order
statistics from the transformed images. Images are then
represented using the extracted texture features. Retrieval
results show, it significantly outperforms the widely used
Gabor texture feature. Platform: |
Size: 1426432 |
Author:Swati |
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Description: 采用matlab，实现了gabor滤波的核心功能-gabor filter is very famous and really useful for texture feature extraction and image retrivel. attached code is wrriten well using matlab. More detail can be referenced in the paper <texture features for browsing and retrieval of image data> Platform: |
Size: 1209344 |
Author:rocky |
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Description: 自动的角点检测算法。运用SIFT特征，对图像中的特征点进行提取！试过，好用！-Automatic corner detection algorithm. The use of SIFT features, right in the image feature point extraction! Tried, easy to use! Platform: |
Size: 4203520 |
Author:Sean |
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Description: 是一种纹理描述算子用于快速提取图像的纹理特征,应用于医学图像检索,场景分类等.-Is a texture description operator for rapid extraction of texture features, used in medical image retrieval, scene classification. Platform: |
Size: 3072 |
Author:zhangliyan |
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Description: 计算机人脸识别技术( Face Reocgnition)就利用计算机分析人脸图像,从中提取出有效的识别信息,用来辨认身份的一门技术。[ 1 ]即对已知人脸进行标准化处理后,通过某种方法和数据库中的人脸样本进行匹配,寻找库中对应人脸及该人脸相关信息。人脸自动识别系统有两个主要技术环节,一是人脸定位,即从输入图像中找到人脸存在的位置,将人脸从背景中分割出来,二是对标准化后的人脸图像进行特征提取和识别。本文中介绍的PCA (特征脸)方法就是一种常用的人脸
特征提取方法。-Computer Face Recognition Technology (Face Reocgnition) on the use of computer analysis of facial image, to extract the valid identification information used to identify the status of a technology. [1] that is known to standardize treatment of face, through a method and a database of face samples for matching, search library, the corresponding face and the face-related information. Automatic face recognition system has two main technical aspects, first, face location, that is, from the input image to find the location of the face there, the faces will be split out from the background, the second is, the standard features of face images extraction and recognition. Described in this paper PCA (Eigenfaces) method is a common facial feature extraction method. Platform: |
Size: 224256 |
Author:Highjoe |
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Description: 这个工程实现了红绿蓝三个分量的提取，采用了新的方法，比传统的方法要清楚些，并且对红色分量做了DFT变换，用模版来对图像进行加密，为图像加密提供了一种新的思路。代码免费下载，功能优。-The project implements the extraction of three components red, green and blue, using a new method to make it clear than the more traditional methods, and components made of red DFT transform, the image used to encrypt the template for the image encryption provides a kinds of new ideas. Code free download, features excellent. Platform: |
Size: 2931712 |
Author:游飞 |
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Description: The early detection of arrhythmia is very important
for the cardiac patients. This done by analyzing the
electrocardiogram (ECG) signals and extracting some features
from them. These features can be used in the classification of
different types of arrhythmias. In this paper, we present three
different algorithms of features extraction: Fourier transform
(FFT), Autoregressive modeling (AR), and Principal Component
Analysis (PCA). The used classifier will be Artificial Neural
Networks (ANN). We observed that the system that depends on
the PCA features give the highest accuracy. The proposed
techniques deal with the whole 3 second intervals of the training
and testing data. We reached the accuracy of 92.7083
compared to 84.4 for the reference that work on a similar
data.-The early detection of arrhythmia is very important
for the cardiac patients. This is done by analyzing the
electrocardiogram (ECG) signals and extracting some features
from them. These features can be used in the classification of
different types of arrhythmias. In this paper, we present three
different algorithms of features extraction: Fourier transform
(FFT), Autoregressive modeling (AR), and Principal Component
Analysis (PCA). The used classifier will be Artificial Neural
Networks (ANN). We observed that the system that depends on
the PCA features give the highest accuracy. The proposed
techniques deal with the whole 3 second intervals of the training
and testing data. We reached the accuracy of 92.7083
compared to 84.4 for the reference that work on a similar
data. Platform: |
Size: 273408 |
Author:Amit Majumder |
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Description: PIVlab - 时间分辨粒子图像测速（PIV）工具：
一种基于GUI的工具，用于预处理，分析，验证，后处理，可视化和模拟PIV数据。
使用MATLAB网络研讨会进行人脸识别代码：
使用MATLAB在线讲座的人脸识别中的主要演示文件。
Gabor特征提取：
该程序生成一个自定义Gabor滤波器组; 并使用它们提取图像特征。
主成分分析：
用于特征提取；
链码：
基于MATLAB的freeman的曲面轮廓描述(PIVlab - time resolved particle image velocimetry (PIV) tool:
A GUI based tool for preprocessing, analysis, validation, post processing, visualization, and Simulation of PIV data.
Using MATLAB webinar for face recognition code:
The main demo file is used in MATLAB online lectures for face recognition.
Gabor feature extraction:
The program generates a custom Gabor filter bank and uses them to extract image features.
Principal component analysis:
For feature extraction;
Chain code:
Surface contour description of Freeman based on MATLAB) Platform: |
Size: 8155136 |
Author:long1219
|
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Search - FEATURES EXTRACTION IN MATLAB