Edge-extraction-

说明：  该课题为基于MATLAB平台的PCA的人脸识别图像考勤系统。传统的人脸识别都是直接人头和人头的对比，现实意义不大，这块都做烂了，不易通过毕设答辩，而且论文不好写。该课题识别原理为：从一副生活照中寻找到人脸，并且分割人脸图象，利用PCA算法进行降维，和库里图片进行对比，输出目标人脸以及记录识别的时间，可以统计人脸打卡的当月次数，从而统计出勤率。该课题还可以继续二次开发，做成库内外人脸的识别，如果是库外人脸则实现报警。GUI界面有清除数据功能，统计工资等功能。(This project is based on the MATLAB platform PCA face recognition image attendance system. The traditional face recognition is the comparison of direct head and head, which is of little practical significance. This part is not easy to pass the final defense, and the paper is not easy to write. The recognition principle of this subject is: find the face from a living picture, segment the face image, reduce the dimension by PCA algorithm, compare with the library picture, output the target face and record the recognition time, and then count the number of times in the month when the face is punched, so as to count the attendance rate. The subject can also be further developed to make face recognition inside and outside the database. If it is outside the database, the alarm can be realized. The GUI interface has the functions of data clearing and salary statistics.)

huffman编码 基于对BMP格式图像的编码！ 具体你们自己看看！(Huffman code)

基于数学形态学的图像颗粒度分析算法，先去噪再求面积然后绘制颗粒度函数。(based on mathematical morphology particle size analysis algorithms, first try to de-noising area before drawing particles function.)

该程序是发表在IEEE上的经典直线提取论文“Extracting Straight Lines”的源代码实现，对计算机视觉、模式识别和信息提取等领域的科学研究人员具有极其重要的参看意义。建议下载学习和适用。(The program is published in the IEEE paper on the classic straight-line extraction " Extracting Straight Lines" the source code implementation of computer vision, pattern recognition and information extraction and other areas of scientific researchers see an extremely important significance. Recommended to download to learn and to apply.)

当前流行的机器学习算法之一：boosting的变体——Gentleboost(The current popular one of machine learning algorithms: boosting variants- Gentleboost)

运用matlab在遥感图象上运用神经网络方法进行图像分类(Using matlab to classify remote sensing images using neural network method)

Latent SVM算法实现行人检测opencv(Latent SVM Pedestrian Detection Based on Algorithms opencv)

DPCM 图像的线性预测编码 有完整的运行界面使用简单(DPCM image of linear predictive coding to run a complete easy to use interface)

针对CMOS 图像传感器输出的Bayer 格式的图像数据, 利用TI 公司的TMS320DM642 数字信号处理器的专用视频端口,可以实现图像捕获、数据传输的无缝连接的特点, 构建了以DM642 为核心的图像实时处理系统。在DM642 中采用两种通用方法(双线性插值、边缘检测) 和文中提出的信号相关的方法, 将从Bayer 公司的CMOS 图像传感器所捕获的8 位Bayer 格式图像数据, 转换为24 位RGB 格式彩色图像数据, 并通过PSNR(信噪比) 和NCD(归一化彩色差异规范) 两种评估方法进行检测。从实验结果可以看出文中提出的方法相对于通用方法提高了图像的信噪比, 锐化图像的边缘, 减少了图像高频信息的错误像素的数量, 提高视觉质量。(Bayer TMS320DM642)

IDL环境下的EVF矢量数据创建，代码清晰。(IDL environment EVF vector data creation, code clarity.)