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: 提出了一种基于特征点的全自动无缝图像拼接方法。该方法采用对于尺度具有鲁棒性的SIFT算法进行特征点的提取与匹配，并通过引导互匹配及投票过滤的方法提高特征点的匹配精确度，使用稳健的RANSAC算法求出图像间变换矩阵H的初值并使用LM非线性迭代算法精炼H，最终使用加权平滑算法完成了图像的无缝拼接。-Based on feature points of automatic seamless image mosaic method. The method used for the scale robust algorithm SIFT feature point extraction and matching, and guide each other through the match and voting methods of filtering feature point improve matching accuracy, the use of robust RANSAC algorithm between images obtained transformation matrix H the initial value and use the LM non-linear iterative algorithm refining H, end-use-weighted smoothing algorithm to complete the image of the seamless splicing. Platform: |
Size: 151552 |
Author:小兔兔牙 |
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Description: 介绍并实现了一套完整的指纹图像预处理方法,通过剩余块处理和平滑方法改进了传统
的指纹图像分割算法 使用方向匹配的方法对指纹图像方向块进行方向滤波完成图像增强 并除去细化后存在的短线和毛刺。该算法对Secugen指纹仪采集的图像和FVC2004数据库中的指纹图像进行实验,结果表明经过预处理后的指纹图像质量得到明显增强,方便进行细节特征提取。-Introduction and realize a complete set of fingerprint image pre-processing methods, and treatment through the remaining block smoothing method to improve the traditional fingerprint image segmentation algorithm using the direction of matching the method of fingerprint image filtering direction the direction of block completion of image enhancement and refinement to remove after the the existence of short-term and burr. The algorithm for fingerprint Secugen Miriam Collection FVC2004 images and fingerprint images in the database to conduct experiments, results showed that after pretreatment of the fingerprint image quality has been markedly enhanced, to facilitate the details of feature extraction. Platform: |
Size: 750592 |
Author:张杰 |
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Description: 影像特征提取是影像匹配和三维信息提取的基础,是影像分析与单像处理技术领域中最重要的任务之一。有效的特
征提取算法是影像分析与处理的关键。从点特征定义出发,叙述了两种常用的点特征提取算子———Moravec算子和Forstner
算子的原理,利用Moravec算子和Forstner算子可以实现影像点特征的提取,并从提取点特征的准确度、提取速度对两种算子
进行比较,最后得出了有益的结论。-Image feature extraction and image matching are three-dimensional information extraction is based on image analysis and single-treatment technology as the most important tasks. Effective feature extraction algorithm for image analysis and processing are the key. Characteristics from the point of definition, describes the two commonly used feature extraction operator points--- Moravec operator and Forstner operator principle, using Moravec Operator and Forstner operator can realize image feature extraction point, and from the extraction point characteristics of accuracy, speed of extraction operator to compare the two, and finally arrive at a useful conclusion. Platform: |
Size: 778240 |
Author:刘镖峰 |
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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: sift特征点提取代码和对两幅图像提取特征点后进行特征点匹配，可用于图像拼接等。c和matlab代码都有-sift feature point extraction code and the two images after the extraction of feature points matching feature points that can be used, such as image stitching. both c and matlab code Platform: |
Size: 375808 |
Author:purple_ice |
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Description: 图像特征提取以及匹配，sift代码。可用于图片检索中，同比SURF，其算法可以较好的识别图像中文字-Image feature extraction and matching, sift the code. Can be used for image retrieval, up by SURF, the algorithm can better identify the image text Platform: |
Size: 25486336 |
Author:sandy |
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Description: sift提取特征点的图像匹配。其中包括特征点的提取和图像匹配两部分-sift feature extraction for image matching. These include feature point extraction and image matching two Platform: |
Size: 334848 |
Author:陈凯 |
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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: 这个程序再matlab2012b版本上调试成功，以前在毕业设计的时候在网上找到的资料，希望对大家有用，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-This program debugging again matlab2012b version is successful, the information at the time of graduation design previously found on the Internet, we want to be useful, MATLAB realize SIFT image feature extraction, and do in different lighting, different perspectives feature matching Platform: |
Size: 1298432 |
Author:李雷 |
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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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Search - image feature extraction and image matching matlab