fingerprint-classification3

重力勘探 频率域重力延拓 二维傅里叶变换 源代码(Gravity Gravity exploration extension frequency domain two-dimensional Fourier Transform source code)

局部二进制模式，LBP，是已被用于纹理特征的一个 分类。在本文中，提出了一种基于使用这些功能的方法 检测缺陷图案的面料。在培训阶段，在第一个步骤LBP算子是 施加到无缺陷织物样品，逐个象素和参考的所有的行（列） 特征矢量的计算。那么这个图像被分为Windows和LBP算子是 应用这些窗口的每一行（列）。根据与参考比较 特征向量一个合适的阈值，无缺陷的窗户被发现。在检测阶段中，一个 测试图像被划分成的窗户，并使用阈值时，有缺陷的窗口可以 检测到。该方法简单，灰度不变。由于其简单性， 线上实现是可能的。(Local Binary Patterns, LBP, is one of the features which has been used for texture classification. In this paper, a method based on using these features is proposed for detecting defects in patterned fabrics. In the training stage, at first step LBP operator is applied to all rows (columns) of a defect free fabric sample, pixel by pixel, and the reference feature vector is computed. Then this image is divided into windows and LBP operator is applied to each row (column) of these windows. Based on comparison with the reference feature vector a suitable threshold for defect free windows is found. In the detection stage, a test image is divided into windows and using the threshold, defective windows can be detected. The proposed method is simple and gray scale invariant. Because of its simplicity, online implementation is possible as well. )

SSD: Single Shot MultiBox Object Detector, in PyTorch A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang, and Alexander C. Berg. The official and original Caffe code can be found here. Table of Contents Installation Datasets Train Evaluate Performance Demos Future Work Reference

关于遥感影像分类和变化检测的一本外文数据，其特色在于用IDL实现了很多经典算法，很值得借鉴！(Foreign language data on a remote sensing image classification and change detection, which feature IDL achieve many classical algorithm, it is worth learning!)

基于otsu的自适应阀值canny边缘检测(adaptive canny edge detection based on otsu)

编程实现小波的边缘检测算法，对图片的边缘处理(Edge Detection Algorithms of Wavelet Based on Programming)

此程序是基于灰度共生矩阵的图像纹理特征提取算法，它进行了四个方向上的灰度共生矩阵的计算，从而得出他们的纹理特征向量，再求均值，使计算进度大幅度提高(This program is based on the GLCM texture feature extraction algorithm, which was four directions GLCM calculation to arrive at their texture feature vector, and then seek means to significantly increase computing progress)

desing and develop a cube rotation

压缩感知重建算法,利用压缩感知理论实现用较少的采样量恢复出高分辨率的图像信息(compressive sensing reconstruction algoriyhm)

图像反卷积 来自D. Krishnan, R. Fergus中提到的方法(image deconvolution The Matlab functions in this directory solve the deconvolution problem in the paper D. Krishnan, R. Fergus: "Fast Image Deconvolution using Hyper-Laplacian Priors", Proceedings of NIPS 2009. )