ImageHistogramEqualization

基于轮廓来寻找流动部分，效果不是很好，但是还可以拿来用(Based on the outline to find the flow part, the effect is not very good, but also can be used with)

数字图像处理中的基本形态学处理，如腐蚀、膨胀、开操作、闭操作等实现的源代码。可以自定义结构元素的形状。(Digital image processing in the basic morphology processing, such as corrosion, swelling, open operation and close operation to achieve the source code. You can customize the shape of structural elements.)

说明：  实现pca主成分分析算法的c语言代码，希望能帮到大家。(Pca principal component analysis algorithm to achieve the c language code, hope to help you.)

小波纹理分析软件.可以进行各种小波分析及图像重建(Wavelet texture analysis software. Can be a variety of wavelet analysis and image reconstruction)

说明：  解决一些图像处理的小问题，具体的划分和问题，文件里有提到(Solve some small problems in image processing)

一个具备线，矩形，椭圆的画图程序，可以设置颜色，宽度，字体(One with lines, rectangles, ellipses drawing program, you can set the color, width, font)

：植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而，低维特征不能全面描述叶片信息，识别准确率低，本文提 出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理，获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征，对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征，对纹理图像提取分形维数，共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相结合的方法对叶片多特征进行特征降维，将叶片高维特征数据降到低维空间。使用降维后的训练样本特征数据对支持向量 机分类器进行训练(plant species identification method is mainly based on blade automatic identification of low dimensional characteristics.However, can not fully describe blade low-dimensional feature information, identification accuracy is low, in this paper A kind of plant leaves recognition method based on multiple feature dimension reduction.First by digital image processing technology to the plant leaf color sample image preprocessing, obtain background color removal, wormhole, petioles, and the blades of a binary image, gray image and texture image.Then the binary image to extract the geometric characteristics and characteristics of structure and characteristics of gray image extraction Hu moment invariants, gray co-occurrence matrix feature, local binary pattern features and Gabor, to extract the fractal dimension of texture image, get 2183 d characteristic parameters.By principal component analysis and linear uation analysis method of combining the characteristics of blade more feature dimensi)

自主选择性的查看一幅图像中的部分区域的颜色直方图：允许用户在一幅图像中选择一个矩形区域，通过按住鼠标键画一个矩形，当鼠标放开是，高亮显示矩形框，同时在另一个独立的窗口中，使用画图函数画一个图表（选定区域的颜色直方图），分别用蓝，绿，红表示选中区域中每种颜色的像素数量。(Self-selective color in an image to view a partial area of ​ ​ the histogram: Allows the user to select a rectangular area in an image by holding down the mouse button to draw a rectangle when the mouse is released, the highlighted rectangle, Meanwhile in a separate window, using the drawing functions to draw a chart (selected color histogram region), respectively, with blue, green, red indicates the number of pixels in the selected area of ​ ​ each color.)

利用opencv工具包的图像缩小程序利用opencv工具包的图像缩小程序利用opencv工具包的图像缩小程序(image shrink with opencv image shrink with opencv image shrink with opencv)

实现图像的滤波、锐化、边缘检测、微分处理及图像平滑(Image filtering, sharpening, edge detection, differential processing and image smoothing)