Description: 摘要：在对粮虫图像处理过程中，介绍了Matlab图像处理工具箱中的函数，给出了图像处理与分析的技术实现, 边缘检测及轮廓提取, 通过形态学方法进行图像特征抽取与分析，达到了比较好的效果.-Abstract : In the right grain pest image processing, introduced the Matlab toolbox image processing functions, given image processing and analysis technology, edge detection and contour extraction, through morphological methods for image analysis and feature extraction, reached a relatively good results. Platform: |
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Author:蓝婧 |
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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: |
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Author:uhih |
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Description: 来自澳大利亚Qeensland大学的计算机视觉Matlab工具箱。
This Toolbox provides a number of functions that are useful in computer vision,
machine vision and related areas. It is a somewhat eclectic collection reflecting
the author s personal interest in areas of photometry, photogrammetry, colorimetry. It
covers functions such as image file reading and writing, filtering, segmentation,
feature extraction, camera calibration, camera exterior orientation, display,
color space conversion and blackbody radiators. The Toolbox, combined
with MATLAB and a modern workstation computer, is a useful and convenient
environment for investigation of machine vision algorithms. It is possible to use
MEX files to interface with image acquisition hardware ranging from simple
framegrabbers to Datacube servers.-from Australia Qeensland University of Computer Vision Matlab toolbox. This Toolbox provides a number of functions tha t are useful in computer vision, machine vision and related areas. It is a somewh at eclectic collection reflecting the author's personal interest in areas of photometry. photogrammetry, colorimetry. It covers functions such as image file reading and writing, filtering, segmentation and feature extraction. camera calibration. camera exterior orientation, display, color space conversion and blackbody radiator s. The Toolbox. MATLAB and combined with a modern workstation c omputer. is a useful and convenient environment for OAS stigation of machine vision algorithms. It is p ossible to use MEX files to interface with image acquisition hardware ranging from simple fram eg Platform: |
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Author:杨愚根 |
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Description: 该源代码为一国外硕士所写，有关虹膜特征提取的部分很有借鉴意义，希望从事图象处理方面研究的各位不要错过．-the source code for an overseas master's written, the iris feature extraction part of a useful one, want to engage in image processing research you should not miss. Platform: |
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Author: |
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Description: 图形图象处理中的一个非常重要的特征的提取算法,zernike矩-Graphic image processing in a very important feature extraction algorithm, zernike Moment Platform: |
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Author:董华丽 |
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Description: 虹膜识别中的特征提取算法：2D-Gabor滤波器算法，将归一化的虹膜图像由此滤波器滤波，可以得到二进制的特征编码。附图片。-Iris recognition in the feature extraction algorithm: 2D-Gabor filter algorithm, the normalized iris image resulting filter can be obtained characteristics of the binary encoding. Attached picture. Platform: |
Size: 958464 |
Author:galaft |
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Description: 基于灰度共生矩阵的纹理特征提取，输出为图像四个方向共十六个特征值-Gray-level co-occurrence matrix based texture feature extraction, the output image in four directions for a total of 16 eigenvalues Platform: |
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Author:chichen |
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Description: 利用Sub-pattern PCA在Yale人脸库上进行人脸识别的matlab源代码，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-pattern PCA use in the Yale face database for face recognition on the matlab source code, 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 the use of 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: 2048 |
Author:章格 |
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Description: 基于非负矩阵分解（NMF）的人脸特征提取算法，NMF基本思想是找到一个线性子空间W，使的构成子空间的基本图像的像素点都是正值，而且人脸图像在子空间上的投影系数也是正数-Non-negative Matrix Factorization (NMF) of facial feature extraction algorithm, NMF basic idea is to find a linear sub-space W, so that the composition of sub-space of the basic image pixels are positive, and face image in the sub-space projection coefficient is positive Platform: |
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Author:李伟 |
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Description: Gabor 滤波器工具箱，包括各种Gabor滤波器的函数，可用于图像滤波处理，特征提取，如人脸，掌纹，指纹识别等。-Gabor filter toolbox, including Gabor filter function, can be used for image filtering processing, feature extraction, such as human faces, palm prints, such as fingerprint recognition. Platform: |
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Author:陈浩 |
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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: 针对高精度的畸变图像,提出了一种基于最小二乘影像匹配的高精度畸变图像矫正算
法. 算法首先利用特征提取与边缘检测对图像进行预处理,并且将特征匹配与最小二乘算法相
结合,从而实现了图像与模板之间精确的子像素定位与匹配. 实验表明,该算法较好的解决了目前高精度畸变图像矫正算法中普遍存在的定位和匹配精度较差的缺陷,图像矫正效果良好,是一种有效的畸变图像矫正算法.-Image distortion for high-precision, a least-squares image matching based on high-precision image distortion correction algorithm. First of all, the use of feature extraction algorithm for edge detection and image pre-processing, and will feature matching with a combination of least-squares algorithm in order to achieve the image and the template between the sub-pixel accurate positioning and matching. The experimental results show that the algorithm has better accuracy of the solution to the current distortion prevalent image correction algorithm to match the accuracy of the positioning and less defects, image correction effect well, is an effective algorithm to correct image distortion. Platform: |
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Author:chenruibao |
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Description: 状是含有高层语义信息的视觉特征，在基于内容的图像检索及图像识别中具有重要的应用价值。有很多种描述子可以描述图像的形状特征，傅立叶描述子可以把二维的图像轮廓信息简化成一维问题进行处理，应用非常广泛。然而自然图像的形状特征通常是杂乱的，有噪声的，提出了一种图像预处理方法，得到净化的形状图像，通过实验研究傅立叶描述子算法提取形状特征的效果。-Abstract Shape is a visual feature which contains intrinsic high-level semantics, and has a great application value in CBIR(Content-Based Image Retrieval) and IR(Image Recognition). There are many descriptors for shape feature. Fourier descriptor predigests 2-demensional image information to 1-demensional signal and be used widely. In fact, the shape of natural image is often messy and noisy. So, this paper proposes a preprocessing method which can clean the noisy shape image, and then researches and analyses the shape feature extraction with Fourier descriptor method with an experiment.
Keywords Shape, Fourier Descriptor, Feature Extraction, CBIR(Content-Based Image R
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Author:倪晓雷 |
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Description: 一本有关特征提取和图像处理的，绝对经典！-One of the feature extraction and image processing, an absolute classic! Platform: |
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Author:zuo |
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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: |
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Author:Swati |
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Description: 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 Platform: |
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Author:zhiminn_wang |
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Search - feature extraction in an image