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LTP_demo-v1

于 2019-01-11 发布

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下载积分: 1 下载次数: 13

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代码说明：

说明：对图像进行纹理特征提取，有LBP，旋转不变lbp，统一lbp，小波特征提取等比较齐全的特征提取算法(Texture feature extraction of images, such as LBP, rotation invariant lbp, unified lbp, wavelet feature extraction and other relatively complete feature extraction algorithms)

文件列表：

LTP_demo-v1\02463d254.pgm, 19515 , 2006-11-23
LTP_demo-v1\02463d282.pgm, 19515 , 2006-11-23
LTP_demo-v1\contents.m, 1537 , 2007-09-18
LTP_demo-v1\demo.m, 4030 , 2008-09-23
LTP_demo-v1\dist_chi2.m, 806 , 2007-09-18
LTP_demo-v1\dist_lbp_disttrans.m, 2557 , 2007-09-17
LTP_demo-v1\fftcoord.m, 435 , 2006-11-26
LTP_demo-v1\GaborFilter.m, 1416 , 2008-04-22
LTP_demo-v1\gauss.m, 125 , 2005-05-24
LTP_demo-v1\gaussianfilter.m, 507 , 2006-12-04
LTP_demo-v1\is_uniform_pattern.m, 236 , 2007-09-17
LTP_demo-v1\lbp_histo.m, 149 , 2007-02-12
LTP_demo-v1\lbp_image.m, 1081 , 2007-09-17
LTP_demo-v1\lbp_image_set0.m, 327 , 2007-09-17
LTP_demo-v1\lbp_image_set2.m, 828 , 2007-09-17
LTP_demo-v1\LICENSE.txt, 23211 , 2007-09-17
LTP_demo-v1\ltp_image.m, 1287 , 2007-09-17
LTP_demo-v1\ltp_image_set0.m, 287 , 2007-09-17
LTP_demo-v1\ltp_image_set2.m, 790 , 2007-09-17
LTP_demo-v1\mask.mat, 845 , 2006-11-27
LTP_demo-v1\preproc2.m, 4291 , 2007-09-17
LTP_demo-v1\README.txt, 973 , 2007-09-18
LTP_demo-v1\uniform_pattern.m, 406 , 2007-09-18
LTP_demo-v1, 0 , 2008-03-24

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插帧
说明：图像处理，通过matlab程序实现视频插帧的功能(Image processing and video frame insertion through MATLAB program)

2020-08-18 15:58:22下载

积分：1
CAGD_NURBS
施法中新版《计算几何与计算机图形学》，书中所带光盘，包含书中源码和其团队开发的软件，能够实现曲线曲面拟合和编辑(The new cast of Computational Geometry and Computer Graphics , the book brought the disc that contains the source code in the book and his team developed software enables curve and surface fitting and edit)

2016-02-15 09:40:33下载

积分：1
AdaBoost_TrainData
这份代码是使用haar+adoboost做人脸检测用的，文件中还包括其他的特征选择，特征提取的算法，对于想做人脸检测这一块的朋友，可以下载来研究。(This code is used haar+adoboost human face detection, the document also includes other feature selection, feature extraction algorithm for face detection which one wants a friend, you can download to study.)

2020-09-13 10:27:58下载

积分：1
Fuzzy-clustering-image-segmentation
模糊聚类的图像分割 C-均值聚类 FCM(Fuzzy clustering image segmentation )

2021-05-09 19:48:34下载

积分：1
duibiduzengqiang
应用于车牌识别中图像增强部分的对比度增强部分！（试了，出的图像效果对比效果比较明显）(License Plate Recognition used in image enhancement part of the contrast enhancement part! (Tried out the effect of the image contrast more obvious))

2008-12-12 22:36:41下载

积分：1
shearlet
Analysis of Singularities and Edge Detection using the Shearlet Transform

2010-01-19 14:51:51下载

积分：1
SensingMatrixDesign
利用块稀疏的方法求解感知矩阵，在压缩感知、图像恢复方面都可以应用(Method for solving block sparse perception matrix in compressed sensing, image restoration can be applied)

2021-04-06 22:29:02下载

积分：1
studyonhighspeedandrealtimestorage
以“宽幅盖面阵立体测绘小相机”项目为课题背景,深入的研究了高速图像传输,图像实时压缩和压缩图像数据的实时存储问题 ATA,fpga("Wide Coverage RUF small, three-dimensional mapping camera," project subject to the background and in-depth study of the high-speed image transmission, Image compression and real-time compression of real-time image data storage problems ATA, fpga)

2007-07-02 11:12:50下载

积分：1
snakedemo
说明：功用：利用snake算法实现数字图像的边缘检测，图像分割以及特征提取(function : use of snake algorithm for digital image edge detection, image segmentation and feature extraction)

2006-05-16 21:05:20下载

积分：1
Code自适应
传统的图像分割方法可以分为基于阈值、边缘、区域的方法等，而传统的分割方法在复杂图像分割中效果不好。为了提高图像分割的性能，我们提出了一种基于局部自适应窗口的Otsu方法。首先，分析了传统阈值法在复杂图像分割中不能很好地形成的原因，比较了全局阈值和局部阈值对图像分割的影响。其次，提出了根据局部信息自适应地改变局部窗口大小的方法，分析了该方法的特点。最后，证明了所提出的新方法优于其他方法。实验结果表明，与其他传统方法相比，该方法能保持更多的细节，获得更满意的结果。(The traditional image segmentation methods can be divided into thresholding, edge and region methods. The traditional segmentation methods do not perform well in the segmentation of complicated images. In order to improve the performance of image segmentation, we propose an adaptive windowed range-constrained Otsu method based on local information.First, the reason why traditional thresholding methods do not perform well in the segmentation of complicated images is analyzed. Therein, the influences of global and local thresholdings on the image segmentation are compared. Secondly, a method of adaptively changing the local window size based on local information is proposed, and the characteristics of the proposed method are analyzed. Finally, the superiority of the proposed method over other methods, It is validated by the experiments that the proposed method can keep more details and acquire much more satisfying results as compared with the other conventional methods.)

2018-10-24 15:04:08下载

积分：1

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