kmeans1

说明：  一、课题介绍 本设计为基于MATLAB的火焰烟雾火灾检测系统。传统的采用颜色的方法，误识别大，局限性强。结合火焰是实时动态跳跃的，采用面积增长率，角点和圆形度三个维度相结合的方式判断是否有火焰。该设计测试对象为视频，通过下一帧和上一帧的差异发现是否有火情，并可发出语音报警。本设计带有一个人机交互式GUI界面，界面友好。是个不错的bishe选题。 二、算法流程 结合火焰的面积增长率，角点和圆形度三个维度综合判断。并且得出每帧图像火焰部分的该三个参数，实时显示在GUI上。 三、GUI界面设计(This design is based on MATLAB flame smoke fire detection system. The traditional method of using color has large error recognition and strong limitation. Considering that the flame is real-time and dynamic jumping, the area growth rate, corner and roundness are combined to determine whether there is flame. The test object of the design is video. Through the difference between the next frame and the previous frame, whether there is fire is found and the voice alarm can be sent out. This design has a personal computer interactive GUI interface, the interface is friendly. It's a good choice for BiShe.)

基于fcm的图像分割方法，效果好，希望能给大家提供一些建议。(FCM-based image segmentation method, the effect of good, I hope everyone can offer some suggestions.)

复杂背景下文字分割程序的源代码，可以很好的对文字进行分割(Text Segmentation in Complex Background program' s source code, can be a good segmentation of text)

Wily book Digital Image processing fundamental dip

基于链码提取的傅立叶描述子,以及傅立叶反变换对图象边界进行重建 (chain code extraction based on Fourier descriptors, and the Fourier transform of image reconstruction border)

使用snake算法寻找图形的轮廓，GVF梯度代替传统方法取得了很好的效果。(Snake algorithm to find the outline of the graphics， GVF gradient instead of the traditional methods achieved good results.)

先进行图像的预处理，采用中值滤波，梯度增强。基于边缘帧差法实现前景检测(first image preproceing，the median filtering，grdient enhancement。based on edge detection method of frame to realiase prospect)

利用FFT傅里叶变换，去除影像中的条带噪声(Removal of image noise)

基于颜色衰减先验模型的单幅图像快速去雾算法。(A Fast Single Image Haze Removal Algorithm using Color Attenuation Prior)

一个基于Gabor滤波器组的多特征融合的图像检索算法（CBIR based on Multi-Features Combining Multi-parameters from Gabor Filter-bank, 简称multi法），融合了基于Gabor 小波系数的标准方差，峰态，能量，平滑度和一致性度量五个特征量度，实验表明，该算法是一种更加有效的图像检索方法。(we propose a CBIR algorithm based on Multi-Features Combining Multi-parameters from Gabor Filter-bank(called multi algorithm for short), which use Gabor filter banks and combine five features including standard deviation, kurtosis, energy, smoothness and uniformity together. The results of experiments show that this algorithm is a more effective method used for image retrieval.)