Description: matlab编的特征匹配，用控制点可以进行匹配。简单的小程序，可直接运行。-Matlab series of the feature matching, control points can be used for matching. Simple small program can be directly run. Platform: |
Size: 1024 |
Author:雷雷 |
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Description: 虹膜识别图象归一化处理，把环形虹膜区域归一为一个统一的矩形图象，方便下一步特征提取和匹配。-Iris recognition normalized image processing, the annular iris region normalized to a uniform rectangular images, the next step to facilitate feature extraction and matching. Platform: |
Size: 4096 |
Author:韩乐 |
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Description: SIFT特征匹配算法是目前国内外特征点匹配研究领域的热点与难点，其匹配能力较强，可以处理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题，甚至在某种程度上对任意角度拍摄的图像也具备较为稳定的特征匹配能力-SIFT feature matching algorithm is the feature points at home and abroad to match the hot area of research and difficult, and its ability to match, can be dealt with between the two images, translation, rotation, affine transformation in case of matching, even in some degree for any angle images also have relatively stable feature matching capacity Platform: |
Size: 3397632 |
Author:ligu |
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Description: 基于投票算法的目标跟踪,基于二阶非线性投票的多目标跟踪算法。该算法通过目标匹配得到同一目标在不同帧中的位置，同时利用特征监测来处理目标的遮挡、分裂问题，并实现目标特征的实时更新。在目标匹配过程中，通过对目标前一帧与当前帧的特征相似性进行投票，得到匹配目标。利用视频图像进行实验，结果表明：该方法对噪声、阴影、遮挡、分裂等具有良好的鲁棒性，较好地实现了多目标的跟踪。-The method used object matching to get objects’ position in different frames, and used feature monitoring to deal with object occlusion, object split and implement real-time update for objects features. Objects were matched based on the similarity voting of their features in successive frames. Experimental study had been carried out using image sequences captured in real scene. The experimental results show that the method is robust against noise, shadows, occlusion, and split and it performs multiple objects tracking finely. Platform: |
Size: 1024 |
Author:崔瑞芳 |
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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: |
Size: 109568 |
Author:chenruibao |
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Description: 基于SIFT的图像配准程序
SIFT特征匹配算法是目前国内外特征点匹配研究领域的热点与难点,其匹配能力较强,可以处理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题,甚至在某种程度上对任意角度拍摄的图像也具备较为稳定的特征匹配能力-SIFT-based image registration procedure is the SIFT feature matching algorithm for matching feature points at home and abroad a hot area of research and the difficulties in matching their ability to deal with translation between two images, rotation, affine transformation to match the case of problems, and even to some extent in any angle images will also be able to match the characteristics of a more stable capacity Platform: |
Size: 617472 |
Author: |
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Description: SIFT特征提取演算法(包含匹配以及除错机制RANSAC)-可用于两张影像之特征点匹配
-SIFT feature extraction algorithm (including the match, as well as debug mechanisms RANSAC)- can be used for two images of the feature points matching Platform: |
Size: 11264 |
Author:qwe |
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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: MATLAB实现图像的SIFT特征提取，并做在不同光照、不同视角下的特征匹配-SIFT MATLAB for image feature extraction, and to do in different lighting, different from the Perspective of feature matching Platform: |
Size: 1291264 |
Author:dulihui |
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Description: 基于matlab平台的harris coener角点检测算法，检测一幅图像中比较突出的特征点，可用于图像匹配或者导航(Harris coener corner detection algorithm based on MATLAB platform detects the salient feature points in an image, which can be used for image matching or navigation) Platform: |
Size: 668672 |
Author:clearlove7
|
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Description: 本文主要对指纹图像进行三方面处理：图像预处理、特征提取和特征匹配。图像预处理包括四个步骤：图像分割、滤波增强、二值化、细化，对指纹图像进行预处理后，去除了原图像的冗余部分，方便后续的识别处理；特征提取主要是提取指纹图像细化后的端点和分叉点；特征匹配是利用两个指纹的图像进行特征点比较，来确定两幅图像是否来自于同一手指。
该课题为基于MATLAB的指纹识别系统，带有丰富的人机交互GUI界面。目前毕业设计选题中，传统指纹识别不易得到高分，基本都是对指纹进行处理，而没有比对两者指纹是不是同一个人，轻易被导师被否决。因此建议做成两个指纹进行比对，输出结果，以文字和声音方式播报结果。整个设计在一个GUI界面上完成。(This paper mainly deals with fingerprint image in three aspects: image preprocessing, feature extraction and feature matching. Image preprocessing includes four steps: image segmentation, filter enhancement, binarization and thinning. After preprocessing fingerprint image, the redundant part of the original image is removed to facilitate the subsequent recognition processing; feature extraction is mainly to extract the endpoint and bifurcation points after thinning fingerprint image; feature matching is to determine two images by comparing the feature points of two fingerprint images Whether it comes from the same finger.) Platform: |
Size: 2781184 |
Author:王春水 |
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Description: 本设计为基于MATLAB的指纹识别系统。本设计系统主要对指纹图像进行三方面处理：图像预处理、特征提取和特征匹配。图像预处理包括四个步骤：图像灰度化、滤波增强、二值化、细化，对指纹图像进行预处理后，去除了原图像的冗余部分，方便后续的识别处理；特征提取主要是提取指纹图像细化后的端点和分叉点；特征匹配是利用两个指纹的图像进行特征点比较，来确定两幅图像是否来自于同一手指。(This design is a fingerprint identification system based on MATLAB. This system mainly deals with fingerprint image in three aspects: image preprocessing, feature extraction and feature matching. Image preprocessing includes four steps: image grayscale, filter enhancement, binarization and thinning. After preprocessing the fingerprint image, the redundant part of the original image is removed for the convenience of subsequent recognition processing. Feature extraction is mainly to extract the endpoint and bifurcation points after thinning the fingerprint image. Feature matching is to determine the two images by comparing the feature points of the two fingerprint images Whether the image comes from the same finger.) Platform: |
Size: 3789824 |
Author:www.wobishe.com |
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Description: 本设计为基于MATLAB的指纹识别系统。带GUI可视化平台。本设计系统主要对指纹图像进行三方面处理：图像预处理、特征提取和特征匹配。图像预处理包括四个步骤：图像灰度化、滤波增强、二值化、细化，对指纹图像进行预处理后，去除了原图像的冗余部分，方便后续的识别处理；特征提取主要是提取指纹图像细化后的端点和分叉点；特征匹配是利用两个指纹的图像进行特征点比较，来确定两幅图像是否来自于同一手指。(This design is based on Matlab fingerprint identification system. With GUI visualization platform. This design system mainly processes fingerprint image in three aspects: image preprocessing, feature extraction and feature matching. Image preprocessing includes four steps: image graying, filtering enhancement, binarization and thinning. After preprocessing the fingerprint image, the redundant part of the original image is removed to facilitate the subsequent identification processing; feature extraction is mainly to extract the refined endpoint and bifurcation point of fingerprint image; feature matching is to determine two images by comparing the feature points of two fingerprint images If it comes from the same finger.) Platform: |
Size: 3466240 |
Author:MATLAB道长 |
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Description: 本设计为基于MATLAB特征点匹配的指纹识别系统。带有一个GUI界面。主要对指纹图像进行三方面处理：图像预处理、特征提取和特征匹配。图像预处理包括四个步骤：图像分割、滤波增强、二值化、细化，对指纹图像进行预处理后，去除了原图像的冗余部分，方便后续的识别处理；特征提取主要是提取指纹图像细化后的端点和分叉点；特征匹配是利用两个指纹的图像进行特征点比较，来确定两幅图像是否来自于同一手指。(This design is a fingerprint recognition system based on MATLAB feature point matching. With a GUI interface. Fingerprint image is mainly processed in three aspects: image preprocessing, feature extraction and feature matching. Image preprocessing includes four steps: image segmentation, filter enhancement, binarization and thinning. After preprocessing the fingerprint image, the redundant part of the original image is removed to facilitate the subsequent identification processing; feature extraction is mainly to extract the refined endpoint and bifurcation point of fingerprint image; feature matching is to determine the two images by comparing the feature points of two fingerprint images Is it from the same finger.) Platform: |
Size: 3682304 |
Author:可乐一生 |
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