资源列表
form
- 次程序可以在form中垂直显示文字，特别是化坐标轴时，写纵坐标的名称-meeting procedures can form vertical display text, especially when the axis of coordinates and write the names of longitudinal coordinates
Test_canto
- 一个画Canto曲线的小程序，希望大家能改进。让程序更完美-a painting Canto curve of the small procedures in the hope that we can improve. Let procedures perfect
blurred_image
- 用来模糊图像，加入一些噪声，并且恢复图像原貌！验证图像的可分辨程度。-used to fuzzy images by adding some noise, image and restore the original appearance. Images can be verified to distinguish degree.
Matlab_longquxian
- 利用此代码可画龙曲线，此代码仅供参考，希望大家学习并改进，-use of this code can be a dragon painted curves, the code for reference purposes only, we hope to learn and improve, thank you
chap3
- 图像处理的matlab源码，无详细说明 图像处理的matlab源码，无详细说明-image processing Matlab source, no detailed descr iption of the image processing Matlab source, No details
Scan_T
- 自己写的一个对PC并口进行的操作程序，以及对数据的读入后，进行的波形显示。（需要硬件支持 D24/56 PCI i/o接口板）-himself wrote a parallel port on PC operating procedures, and to read into the data, the waveform shows. (D24/56 need hardware support PCI i / o interface board)
icontobmp
- 将图标转换位位图，效果很好，速度很快，改动后可完成批量转换-icon will change places bitmap and the results very good, very fast, can be altered after the completion of batch conversion
xuanzhuan
- 旋转立方体绘制，效果很好，拓展后可开发相应的例子-rotating cube mapping, a good effect, and can expand the development of the corresponding example
shap
- 画几何图形，圆弧，弦，椭圆，圆饼，矩形多边形，多义线-painting geometry, arc, chord, oval, round cake, rectangular polygon, multi-line
sine
- delphi画正弦曲线，抛砖引玉，发挥后可完成绘图的一些功能-delphi painting sine curve, something to play after the completion of some functional mapping
PCA+LDA.Class.vc
- 结合PCA+LDA的图像识别算法VC封装类,PCA（主元素分析，光照敏感）,可用于人脸识别的初级算法-combination of image recognition algorithm VC Packaging category, PCA (principal component analysis, Light-sensitive), can be used for the initial face recognition algorithm
K_Average
- 简单的模式识别的分类算法（K_均值算法），适用于各种识别算法的基础分类算法--详细信息见说明-simple pattern recognition classification algorithm (K_ means algorithm), apply to the recognition algorithm based classification algorithm -- detailed information, see Note