signalprocessing

说明：  图片自适应二值化处理，二值化处理使用简单方便。(Adaptive binarization image processing, binary processing easy to use.)

这是一种对TV模型算法的一种快速改进算法，C++实现，在Code::Blocks下编译成功(This is a TV model algorithm for a fast algorithm, C++ achieve, in the Code :: Blocks compile successfully under)

一种新的彩色图像去噪与增强模型(A new color image denoising and enhancement model)

连续投影算法的Matlab程序 下载后可以直接使用(Successive projections algorithm )

说明：  NISwGSP stitching . 新一代的图像拼接(image stitching new. more powerful than apap)

c# Ico图片文件转换成 bmp格式 实例源码

MATLAB去雾算法程序，内附去雾图片，完全可以运行。(MATLAB fog removal algorithm program, attached to the fog picture, can run.)

指纹图像因设备、图像增强处理等原因造成的纹线断裂会产生伪特征点,会对指纹识别产生负面影响。在结 合传统方法优点的同时,针对间距大、方向偏移小和间距大、方向偏移大的断裂情况,本文设计出窗口制约法和改进的 窗口制约法2 种不同的修复方法。实验结果表明,该方法使修复更加全面、完整,提高了伪特征点去除率,易于编程实 现,对细化指纹图像的断裂有很好的修复效果。(The broken ridge fingerprint image processing equipment, image enhancement and other causes will generate pseudo-feature points to be a negative impact on fingerprint identification. While combining the traditional method has the advantage, for the spacing, direction offset small spacing, direction offset large fracture situation, this design window constraints window method and the improved two kinds of constraints, different repair methods. Experimental results show the method to fix a more comprehensive and complete removal of pseudo-feature points, easy to program, well thinned fingerprint image fracture repair.)

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.)

说明：  采用gabor算法，灰度共生矩阵、灰度梯度共生矩阵提取图像纹理信息(Using Gabor algorithm, gray level co-occurrence matrix and gray level gradient co-occurrence matrix to extract image texture information)