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灰度共生矩阵、灰度梯度共生矩阵提取纹理特征(Gray Level Co-occurrence matrices, gray-gradient co-occurrence matrix texture features extracted)

对玻璃表面缺陷图像进行处理，进行分类识别(The glass surface defect image processing, classification and identification)

基于数学形态学实现振动信号降噪。研究了数学形态滤波器对振动信号在不同类型、不同强度噪声干扰下 的降噪能力，提出了采用开一闭和闭一开组合数学形态滤波器实现旋转机械振动信号降噪处理的方法。通过仿真 计算及实例，检验了形态滤波器的滤波效果，表明数学形态滤波器可以有效剔除脉冲、降低随机噪声干扰，提高 振动信号的信噪比。(The vibration signal noise reduction based on mathematical morphology. Mathematical morphology filter vibration signals in different types, different intensity noise, noise reduction capabilities, proposes using open-closing and close the opening combination of mathematical morphology filter rotating machinery vibration signal noise reduction processing. Simulation and examples, test the morphological filters filtering effect, indicating that the mathematical morphological filter can effectively excluded the pulse, to reduce random noise and improve the signal-to-noise ratio of the vibration signal.)

说明：  一个纹理坐标自动生成的例子，有助于理解纹理坐标自动生成的各个函数(An example of automatically generated texture coordinates, texture coordinates generated automatically help you understand the various functions)

实现LLE算法，本算法是改进的LLE算法，主要是针对人脸图像的。()

通过matlab实现对视频的实时提取及处理(Real-time extraction and processing of the video by matlab)

说明：  利用直方图均衡可以将对对比图进行调整，增强局部的对比度，特别在图像有用对比度相当接近的情况，直方图均衡可以很好的增强对比度使得图像的细节更清晰，达到图像增强的目的。(Histogram equalization can be used to adjust the contrast graph to enhance the contrast of the local image, especially in the case that the useful contrast of the image is quite close. The histogram equalization can improve the contrast degree so that the details of the image are clearer and the purpose of image enhancement is achieved.)

实现不规则形状碎纸片的拼接，并展示出原图像(The splicing of irregular shaped pieces of paper is realized and the original image is displayed.)

形状上下文算法用于图像检索，程序中已运用了.mat文件存储图像库中的图像特征，检索效果很好。(shapecontext is used to realize imgage retrival,it shows very effective performance.)

ELMAN计算方法，改进的算法,非常好用(ELMAN calculation algorithm, the improved，use very well)