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RANSAC+SURF

于 2021-03-03 发布文件大小:430KB

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下载积分: 1 下载次数: 11

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代码说明：

基于SURF算法实现图像特征提取与描述，使用RANSAC进行图像细配准(SURF algorithm was used to extract and describe image features, and RANSAC was used for image registration)

文件列表：

RANSAC%2BSURF\example.m, 2015 , 2019-04-24
RANSAC%2BSURF\lena1.png, 239755 , 2010-09-07
RANSAC%2BSURF\lena3.png, 182741 , 2019-04-24
RANSAC%2BSURF\license.txt, 1335 , 2010-09-06
RANSAC%2BSURF\OpenSurf.m, 3778 , 2010-09-07
RANSAC%2BSURF\Ransac.m, 1799 , 2012-12-01
RANSAC%2BSURF\SubFunctions\FastHessian_BuildDerivative.m, 603 , 2010-07-27
RANSAC%2BSURF\SubFunctions\FastHessian_buildResponseLayer.m, 1699 , 2010-07-30
RANSAC%2BSURF\SubFunctions\FastHessian_buildResponseMap.m, 1877 , 2010-07-21
RANSAC%2BSURF\SubFunctions\FastHessian_getIpoints.m, 2353 , 2010-07-30
RANSAC%2BSURF\SubFunctions\FastHessian_getLaplacian.m, 455 , 2010-07-27
RANSAC%2BSURF\SubFunctions\FastHessian_getResponse.m, 450 , 2010-07-27
RANSAC%2BSURF\SubFunctions\FastHessian_interpolateExtremum.m, 2478 , 2010-07-30
RANSAC%2BSURF\SubFunctions\FastHessian_isExtremum.m, 1680 , 2010-07-30
RANSAC%2BSURF\SubFunctions\FastHessian_ResponseLayer.m, 738 , 2010-07-30
RANSAC%2BSURF\SubFunctions\IntegralImage_BoxIntegral.m, 791 , 2010-07-29
RANSAC%2BSURF\SubFunctions\IntegralImage_HaarX.m, 494 , 2010-07-30
RANSAC%2BSURF\SubFunctions\IntegralImage_HaarY.m, 556 , 2010-07-30
RANSAC%2BSURF\SubFunctions\IntegralImage_IntegralImage.m, 796 , 2010-07-29
RANSAC%2BSURF\SubFunctions\PaintSURF.m, 1089 , 2010-07-30
RANSAC%2BSURF\SubFunctions\SurfDescriptor_DecribeInterestPoints.m, 1554 , 2010-07-31
RANSAC%2BSURF\SubFunctions\SurfDescriptor_GetDescriptor.m, 3636 , 2010-07-31
RANSAC%2BSURF\SubFunctions\SurfDescriptor_GetOrientation.m, 2921 , 2010-07-31
RANSAC%2BSURF\WarpFunctions\affine_warp.m, 9721 , 2010-09-07
RANSAC%2BSURF\SubFunctions, 0 , 2019-04-24
RANSAC%2BSURF\WarpFunctions, 0 , 2019-04-24
RANSAC%2BSURF, 0 , 2019-04-24

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cvpr01_zollei1109
医学图像配准，医学图像2D_3D配准，基于vc++开发。(The registration of pre-operative volumetric datasets to intra-operative two-dimensional images provides an im- provedway of verifying patient positionandmedical instru- ment location. In applications from orthopedics to neuro- surgery, it has a great value in maintaining up-to-date in- formation about changes due to intervention. We propose a mutual information-based registration algorithm which es- tablishes the proper alignment via a stochastic gradient as- centstrategy. Ourmaincontributionliesinestimatingprob- ability density measures of image intensities with a sparse histogrammingmethodwhichcouldlead to potentialspeed- up over existing registration procedures and deriving the gradient estimates required by the maximization procedure. Experimental results are presented on fluoroscopy and CT datasets of a real skull, and on a CT-derived dataset of a real skull, a plastic skull and a plastic lumbar spine seg- ment.)

2014-09-09 16:29:28下载

积分：1
fuzzyCompute
基于模糊理论的图象处理,有图象增强,图象平滑和边缘检测算子.()

2007-07-16 18:18:40下载

积分：1
LISQ
说明：利用红黑小波进行图像去噪，图像复原，并与常规的小波进行比较(use red, black and wavelet denoising images, image recovery, and with the conventional comparison of wavelet)

2006-03-28 20:11:55下载

积分：1
splitimg
自己编的利用FreeImage库分割图像的程序,可以将一个图片分成5个不同区域的图片,主要用于壁纸分割.(Own use FreeImage library image segmentation procedure, a picture can be divided into five different regions of the picture, the main partition for wallpaper.)

2009-03-19 19:31:01下载

积分：1
RSFoBa-Demo
一种效果比较好的高光谱解混算法，模拟数据以及真实数据的实验都在，直接可以跑。(An effect good hyperspectral unmixing algorithm, experimental simulation data and real data are in, you can directly run.)

2016-04-20 16:12:39下载

积分：1
MATLAB_
能够实现对生物芯片的识别和图像处理，识别有效芯片区域，读取阴性和阳性点分布和数量。(It can realize the recognition and image processing of biochip, identify the effective chip area, read the distribution and number of negative and positive points.)

2020-07-17 21:08:48下载

积分：1
LDA-based-face-recognition
基于LDA的人脸识别技术，从ORL数据库读数据，然后从中取一部分进行训练，一部分进行测试。(This code is LDA base face recognition programme. It reads nots faces from ORL database and the rest (noc-nots) are used as test. LDA_Performance shows the recognition performance. )

2009-03-25 16:39:23下载

积分：1
two
：植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而，低维特征不能全面描述叶片信息，识别准确率低，本文提出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理，获得去除颜色、虫洞、叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征，对灰度图像提取 Hu不变矩特征、灰度共生矩阵特征、局部二值模式特征和 Gabor 特征，对纹理图像提取分形维数，共得到 2183 维特征参数。再采用主成分分析与线性评判分析相结合的方法对叶片多特征进行特征降维，将叶片高维特征数据降到低维空间。使用降维后的训练样本特征数据对支持向量机分类器进行训练(plant species identification method is mainly based on blade automatic identification of low dimensional characteristics.However, can not fully describe blade low-dimensional feature information, identification accuracy is low, in this paper A kind of plant leaves recognition method based on multiple feature dimension reduction.First by digital image processing technology to the plant leaf color sample image preprocessing, obtain background color removal, wormhole, petioles, and the blades of a binary image, gray image and texture image.Then the binary image to extract the geometric characteristics and characteristics of structure and characteristics of gray image extraction Hu moment invariants, gray co-occurrence matrix feature, local binary pattern features and Gabor, to extract the fractal dimension of texture image, get 2183 d characteristic parameters.By principal component analysis and linear uation analysis method of combining the characteristics of blade more feature dimensi)

2017-02-28 09:57:50下载

积分：1
DCT
基于DCT域的数字水印算法主要包括水印调制、水印嵌入和水印提取，首先在嵌入载体图像之前用Logistic混沌序列对水印进行调制，得到一个只有+1和-1随机序列的水印，同时将载体图像进行全局DCT变换，然后将水印图像嵌入人类视觉系统最重要的部分，即DCT最大的系数，DC（Direct Current）部分也包含在这最大的系数中，这部分的系数满足人类视觉特性，会使水印嵌入的性能更好。嵌入算法是将水印与这些系数进行相乘获得新的系数，再用新的系数来替换原来的系数，即获得嵌入水印后的离散余弦域的图像，然后对这个变换后的图像进行IDCT，就会得到需要的水印图像。(While the carrier image digital watermarking algorithm based on DCT domain include watermark modulation, watermark embedding and watermark extraction, the first of the watermark embedded in a carrier modulated image before using Logistic chaotic sequence, only+1 and-1 to get a random sequence of watermark, Global DCT transform, then the watermark image is embedded most important part of the human visual system, i.e. the largest DCT coefficients, DC (Direct Current) in this section also contains the largest coefficient, the coefficient of this part of the human visual characteristics to meet, make watermarks Embed better performance. The watermark embedding algorithm is with these coefficients are multiplied to obtain new coefficients, and then a new factor to replace the original coefficients, namely discrete cosine domain to obtain an image watermarked and then transformed the image of this conduct IDCT, on watermark image will be needed.)

2015-03-24 17:13:25下载

积分：1
0301
图像配准和拼接，肯定可以使用。。。harris+ransac(Image registration and stitching, they can definitely use. . .)

2011-07-14 11:28:30下载

积分：1

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