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Description: 基于surf的图像特征的提取，采集，配准已经图像融合拼接技术的研究-Image feature extraction surf-based acquisition, registration has been studied image fusion splicing technology
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Size: 7061504 |
Author: heyanyan |
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Description: SURF 图像特征点快速提取法还有描述，可用于迅速匹配两张图片中的特征点-SURF image feature points extraction method also described fast, can be used to quickly match the image feature points in the two
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Size: 719872 |
Author: sleangao |
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Description: 运用matlabr2012a,实现SURF算法的图像特征提取和匹配。-Use matlabr2012a, SURF algorithm for image feature extraction and matching.
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Size: 5002240 |
Author: 李鹄 |
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Description: 本程序采用基于快速鲁棒特征点的图像拼接技术，该技术与其他图像拼接技术相比，具有鲁棒性好的特点，对图像序列中的光照变化、尺度变化、旋转变化具有良好的适应性；与基于SIFT特征点的图像拼接技术相比，其拼接速度更快。-This program uses a fast and robust image mosaic technology based on feature points, compared with the other image mosaic technology, has good robustness on image sequences, illumination changes, scale changes, rotation changes has good adaptability compared with the image stitching based on SIFT feature points, the splicing speed.
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Size: 359424 |
Author: 李争 |
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Description: 对两幅图像进行配准，分别提取两幅图像的surf特征点以及描述子，得到粗匹配结果，然后根据粗匹配结果，采用ransac方法计算基础矩阵，并去除误匹配点，得到较准确匹配结果-Two image registration, surf was extracted from the feature points in two images to get the coarse matching and descriptor, then according to the results, the coarse matching results, using RANSAC method to calculate the fundamental matrix, and eliminate the error matching, gain a more accurate matching results
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Size: 108544 |
Author: 王奇 |
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Description: 基于SURF算法的特征提取代码，里面包含一些图像处理算法，opencv2.3.1和vs210-Feature extraction based on SURF algorithm code, containing some image processing algorithms, opencv2.3.1 and vs210
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Size: 21665792 |
Author: cold |
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Description: SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。
采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。
-SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching.
This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching.
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Size: 2070528 |
Author: 马丁 |
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Description: 基礎SURF應用從最簡單的入門找特徵點、到稍微進階的影像比對以及照片合成全景圖的應用-SURF application of basic applications, from the simplest to find entry feature points to a slightly advanced image comparison and synthesis panorama photo
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Size: 25830400 |
Author: 蔡秉嘉 |
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Description: This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a distribution-based descriptor) and by simplifying these methods to the essential. This leads to a combination of novel detection, description, and matching steps. The paper presents experimental results on a standard uation set, as well as on imagery obtained in the context of a real-life object recognition application. Both show SURF’s strong performance.
-This is achieved by relying on integral images for image convolutions by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a distribution-based descriptor) and by simplifying these methods to the essential. This leads to a combination of novel detection, description, and matching steps. The paper presents experimental results on a standard uation set, as well as on imagery obtained in the context of a real-life object recognition application. Both show SURF’s strong performance.
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Size: 680960 |
Author: Amal |
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Description: Module Provides implementation of SURF Points to detect invariant features input image for robust image matching. It takes less time to detect features an image rather than SIFT-Module Provides implementation of SURF Points to detect invariant features input image for robust image matching. It takes less time to detect features an image rather than SIFT
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Size: 49152 |
Author: yuvaraj |
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Description: 对搞图像拼接的人很有帮助，经典之作，希望对你有用-To make image mosaicing is helpful, classic, hope useful to you
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Size: 2213888 |
Author: 1233 |
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Description: SURF图像匹配程序，代码需要vs + opencv， 实测vs2013+opencv2.4.10可用-SURF image matching the code needs vs+ opencv, the measured vs2013+opencv2.4.10 available
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Size: 443392 |
Author: 林林 |
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Description: 用于图像特征提取和匹配，三维重建等的经典方法，包括sift，surf，Harris，RANSAC,8点算法等-For image feature extraction and matching, 3D reconstruction and other classical methods, including sift, surf, Harris, RANSAC, 8 point algorithm, etc.
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Size: 9069568 |
Author: 陈美美 |
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Description: 本算法基于MATLAB，用于将两幅以上的图像进行融合处理，达到增强图像目的等-The algorithm based on MATLAB, for more than two image fusion process, to achieve the purpose of enhancing the image and so on
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Size: 1829888 |
Author: 赵雨晴 |
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Description: surf特征的检测程序，提取图像中的surf特征-surf feature detection program, surf to extract image features
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Size: 13280256 |
Author: 孙明军 |
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Description: 特征点提取与匹配，很好的一种图像配准算法-Feature point extraction and matching, a good image registration algorithm
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Size: 1425408 |
Author: 卢冰 |
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Description: SURF意指 加速的具有鲁棒性的特征，由Bay在2006年首次提出，这项技术可以应用于计算机视觉的物体识别以及3D重构中。SURF算子由SIFT算子改进而来，一般来说，标准的SURF算子比SIFT算子快好几倍，并且在多幅图片下具有更好的鲁棒性。SURF最大的特征在于采用了harr特征以及积分图像integral image的概念，这大大加快了程序的运行时间。-SURF (Speeded Up Robust Feature) is a robust local feature detector, first presented by Herbert Bay et al. in 2006, that can be used in computer vision tasks like object recognition or 3D reconstruction. It is partly inspired by the SIFT descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. SURF is based on sums of 2D Haar wavelet responses and makes an efficient use of integral images.
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Size: 2418688 |
Author: 草 |
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Description: 使用opencv检测图像特征，并进行特征点的匹配。输入两幅图像，得到特征参数-Using opencv image feature detection and matching feature points. Two input image characteristic parameter obtained
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Size: 540672 |
Author: mary |
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Description: detect a key point for image using SURF with opencv
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Size: 2048 |
Author: ayadi |
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Description: image registration by sift and surf
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Size: 3067904 |
Author: 花卷 |
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