生物特征识别技术手指静脉识别技术_余成波

对采样得到的180幅断层图像进行重建，并针对其中的一幅图像进行处理，并且统计图像中颗粒的大小和数目！(Tomographic images of 180 samples obtained were rebuilt, and for which an image processing and image size and number of particles statistics!)

实现了立体匹配的SAD算法计算视差图，结果比较理想(Using the SAD algorithm to calculate the disparity map of stereo matching, the result is good.)

基于旋转运动的微多普勒模型的建立，对于了解微多普勒的学习者有帮助。(The establishment of micro-Doppler model based on the rotational motion, help learners understand the micro-Doppler.)

PCNN 灰度图像，图像分割matlab程序(PCNN_GrayImage_Segmentation)

一种利用中心和结构聚类的稀疏表示图像去噪方法，有不错的效果(a image denoising method with structral clustering and sparse representation, has good effect .)

基于C++的人脸分割的设计，C／Ｃ++语言、数字信号处理，最好选修过“数字图像处理”。(Based on the C++ face segmentation design, C/C++ language, digital signal processing, the best elect digital image processing.)

说明：  该压缩包内含有基于梯度金字塔变换的多模态图像融合方法的MATLAB代码，可以直接运行，得到融合结果。另外，压缩包内包括了多组已配准、待融合的图像示例，具体包括红外图像与可见光图像、CT与MR图像，多聚焦图像。本人还对代码进行了必要的解释。推荐下载(The compression package contains matlab code of multimodal image fusion method based on gradient pyramid transformation, which can be run directly to get fusion results. In addition, the compressed package includes several groups of images that have been registered and to be fused, including infrared images and visible images, CT and MR images, and multi focus images. I also gave the necessary explanation to the code. Recommended download.)

说明：  详细介绍了多普勒天气雷达系统建模与仿真应用 (Details of the Doppler Weather Radar System Modeling and Simulation Application)

说明：  本设计为基于MATLAB的指纹识别系统。本设计系统主要对指纹图像进行三方面处理：图像预处理、特征提取和特征匹配。图像预处理包括四个步骤：图像灰度化、滤波增强、二值化、细化，对指纹图像进行预处理后，去除了原图像的冗余部分，方便后续的识别处理；特征提取主要是提取指纹图像细化后的端点和分叉点；特征匹配是利用两个指纹的图像进行特征点比较，来确定两幅图像是否来自于同一手指。(This design is a fingerprint identification system based on MATLAB. This system mainly deals with fingerprint image in three aspects: image preprocessing, feature extraction and feature matching. Image preprocessing includes four steps: image grayscale, filter enhancement, binarization and thinning. After preprocessing the fingerprint image, the redundant part of the original image is removed for the convenience of subsequent recognition processing. Feature extraction is mainly to extract the endpoint and bifurcation points after thinning the fingerprint image. Feature matching is to determine the two images by comparing the feature points of the two fingerprint images Whether the image comes from the same finger.)

利用迭代残差插值的去马赛克算法，进一步减小估计误差，得到更准确的全彩色图像，性能很不错。(Iterative interpolation residuals demosaicing algorithm to further reduce the estimation error, more accurate full-color images, the performance is very good.)