tracker_release2

关于指纹图像处理的有关论文资料，希望各位同仁多多 指教。(Fingerprint image on paper deal with the relevant information, I hope that Tongren exhibitions.)

一个医学图像配准的源程序，希望对大家有用(A medical image registration of the source, in the hope that useful to everybody)

a lane dtection method using hough-transform

一些matlab图像图像处理例程,骨架,灰度图像梯度,凸壳,细化.(Some image image processing matlab routines, skeleton, grayscale gradient, convex hull, thinning.)

一.主站说明 本站主站为HTM格式，主要用背景图片添加内容.使用简单方便，只要会PHOTO　SHOP　的朋友均应会自已添加站内的内容.在此就不多说了.(A main station that the main station for the HTM format, the main use of the background picture to add content.Easy to use, as long as PHOTO SHOP friends should be added to the content of their own station.)

已知一图像的轮廓，计算该轮廓质心，并标注在图上(A known the outline of image, the contour centroid calculation, and marked on the map )

压缩文件是CNN卷积神经网络图像处理的数据库mnist_uint8.mat(Compressed file is the database of CNN convolution neural network image processing mnist_uint8.mat)

图像检测的算法，Faster R-CNN算法，先对整张图像进行卷积计算，然后通过感兴趣区域池化层(RoI Pooling Layer)将选择性搜索算法推荐出来的候选区域和卷积网络计算出的特征映射图进行融合，得到候选区域对应的特征矢量，这种共享卷积计算的操作极大地减少了卷积计算的次数。而且这些特征矢量的维度统一，方便后续的分类工作。通过感兴趣区域池化层处理卷积特征，并将得到的特征送往两个并行计算任务进行训练，分类和定位回归。通过这些方法和改进的框架，Fast R-CNN 用更短的训练和测试时长，取得了比 R-CNN 更好的效果(Faster R-CNN algorithm first convolutes the whole image, then fuses the candidate regions recommended by the selective search algorithm and the feature mapping maps calculated by the convolution network through the RoI Pooling Layer to get the corresponding feature vectors of the candidate regions, which greatly reduces the number of convolution calculations. Moreover, the dimension of these feature vectors is unified, which facilitates the subsequent classification work. The convolution feature is processed by the pooling layer of the region of interest, and the obtained feature is sent to two parallel computing tasks for training, classification and positioning regression. Through these methods and improved framework, Fast R-CNN uses shorter training and testing time and achieves better results than R-CNN.)

人脸识别matlab源代码，应用主分量分析（PCA）实现了人脸识别。(Face recognition matlab source code, application of principal component analysis (PCA) to achieve a face recognition.)

遥感图像融合，通过多个指标对融合图像进行评价，比较优劣。(remote sensing image fusion, through the integration of a number of indicators to evaluate images, and compared them.)