Handbook-of-Machine-Vision

说明：  用GUI实现sin画图，输入数据，曲线动态显示(Drawing sin with GUI)

这是一个有界差分方法进行分割的例子，对于学习数学图像处理的同学，有启发作用(This is a difference method has industry segmentation example, for image processing mathematics students, has inspired the role of)

sift角点检测及匹配，在不同尺度空间下的角点检测方法，很方便实用。(sift corner detection and matching, the corner detection methods under different scales of space, it is convenient and practical.)

标准Hough检测圆，在数字图像中检测圆形目标，需要先边缘提取，在二值图像中检测圆。(circle detection using standard hough transform )

基于PCNN的特征提取,PCNN用于特征提取时，具体平移、旋转、尺度、扭曲等不变性，这正是许多年来基于内容的图像检索系统追求的目标，同时PCNN用于特征提取时，有很好的抗噪性。而且PCNN直接来自于哺乳动物视觉皮层神经的研究，具有提取图像形状，纹理，边缘的属性。用PCNN能很好地对图像进行签名，将二维的图像的特征提取成一维矢量签名。(Feature extraction of specified object is an important preprocessing stage in machine vision systems. In this paper, we present a novel hybrid feature extraction method using PCNN (Pulse Coupled Neural Network) and shape information. First, we use PCNN firing map train to formulate object’s time signature, then we use roundness of each firing map to formulate object’s shape information vector, the final feature matrix we got is combined time signature and roundness. We take correlations as our judge criteria in our experiments. It has been proved that the algorithm is not sensitivity with the rotation, scaling and translation of the object and is a useful method for target recognition applications.)

寻找harris角点 利用ssd匹配角点(finding and matching harris points)

基于纹理特征的图像检索源码，用双树复小波（DT－CWT）三级分解提取图像的纹理特征(Texture-based image retrieval source code, using dual tree complex wavelet (DT-CWT) to extract texture features three levels of decomposition)

实现一个高精度指针仪表读数自动识别系统．用数码摄像头采集仪表的图像，然后利用数字图像处理技术识别刻度和指针，根据指针和刻度的相对位置计算指针读数值．使用条件霍夫变换（Constrained HOUGH Transfer）和中心投影分析法实现刻度的全自动识别，采用快速中心投影法进行指针检测与识别，识别速度达到68ms．实验结果表明该方法比传统方法速度快、精度高，系统读数平均误差仅为0．016％(To achieve a high precision automatic identification system pointer meter reading. Instrument with a digital camera capture images, then using digital image processing technology to identify scale and pointer, pointer and scale according to the relative position of the pointer readings calculated. Use Hough transform (Constrained HOUGH Transfer) and center projection analysis method to achieve scale automatic identification method using fast center projection target detection and recognition, recognition speed of 68ms. Experimental results show that faster than traditional methods, high accuracy, the system average error of only 0.016 of reading)

二维线性判别 功能比较强 二维线性判别 功能比较强(Img = imread( twoObj.bmp ) )

说明：  关于图像修复的一个程序可以实现TV模型的图像修复(Image restoration of TV model can be realized)