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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
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一种图像检索中纹理特征提取的方法。本文介绍了基于Gabor 滤波器和Gabor 小波变换提取纹理特征的分析方法, 以及对Gabor 小波进行了高斯归一化以提高对图像检索的速度和准确度。-An image retrieval texture feature extraction methods. This article based on Gabor filters and Gabor wavelet transform to extract texture feature analysis me
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Feature Extraction of Infrared Target Based on Image Moment and Wavelet Energy
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图像检索中颜色的特征提取及匹配算法，以家权欧几里得距离，中心距得加权距离，直方图交集算法等。-Image Retrieval color feature extraction and matching algorithm to the right home Euclid distance, center distance of a weighted distance, histogram intersection algorithm.
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Based on the information processing functionalities of spiking neurons, a spiking neural network model is proposed to extract features from a visual image. The network is constructed with a conductance-based integrate-and-fire neuron model and a set
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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 accu
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介绍BEMD用于图像特征提取的一篇文章，对这方面有研究的可以-Introduction BEMD for image feature extraction in an article in this respect, the study can look at
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These source codes are for image feature extraction in Matlab
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Code for Texture Extraction
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图像中角点(特征点)提取与匹配算法.，通过harris焦点检测来实现特征的提取-Extraction and matching algorithms of image corners (feature points), harris focus detection to the feature extraction
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ieee论文，主要是高分辨率SAR图像的特征提取与检索技术-ieee papers, mainly high-resolution SAR image feature extraction and retrieval technology
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基于图像内容的多维特征检索技术，主要利用图像的形状特征提取-Retrieval technique based on multi-dimensional characteristics of the image content, the main use of the shape of the image feature extraction
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xray image feature extraction using bps
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利用opencv对几种图像特征的提取方法，进行总结实现。-Use opencv on several kinds of image features extraction method, summarizes implementation.
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把 SIFT 算法应用在牙齿模型图像上，检测牙齿图像的特征点。 方法：首先采用高斯差分算子 DoG 搜索整个图
像的尺度和位置信息，从而确定具有代表性尺度、方向的特征点。基于其稳定性选择关键点，得到一个详细的模型以确定每个候
选点的合适位置和范围。基于局部图像梯度方向信息将方向矢量和关键点对应起来。在选定范围内的每个关键点周边区域测量
局部图像梯度，并采用 KNN 算法进行特征匹配。 结果：通过大量的实验和与其他特征提取方法相比较，该方法能有效地检测牙
齿模型图像的特征，并为牙齿
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彩色图象的特征提取与计算软件设计说明书。说明书中介绍了一些彩色图象的特征提取方法，包括颜色、纹理、特征点的提取，另外还介绍了几种图像分割的方法。-This is a color image feature extraction and calculation software design specification.This paper based on color and texture, methods of extracting feature points, and some imag
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一篇关于图像纹理提取的经典文章，涉及图像处理领域的方向动态！-An article about the classic image texture extraction, involves the direction in the field of dynamic image processing.
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this code willlbe use for image feature extraction okayy don
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作为一种优秀的纹理特征提取技术，多重分形谱插值方法被提出用于图像的特征提取和分类。-As an excellent texture feature extraction technology, a multi-fractal spectrum interpolation methods have been proposed for image feature extraction and classification.
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详细介绍了数字图像的基本特征，包括直方图、特征提取、目标识别、图像分割与复原、形态学图像处理等相关知识(Describes in detail the basic features of digital images, including histogram, feature extraction, target recognition, image segmentation and restoration, morphological image processing and other re
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