bemd

I WANT SOURCE CODE FOR IMAGE SEGMENTATION

非下采样轮廓波变换与二维主分量分析的循环模式计算(nonsubsambled contourlet transform and two dimensional principle component analysis cycle module calculation)

基于OPCV的blob搜索算法，图像处理经典算法(OPCV the blob-based search algorithm, image processing, the classical algorithm)

推荐火灾检测的参考文献，有火焰多个特征提取的算法。(the article is about how to detect fire，using many algorithms to get the features of fire.)

VC6.0环境下使用可视化工具VTK 实现三维重建方法是光线投影法，实现效果较好(3D-reconstruction)

背景音乐只是随便写了写,具体的可以改数组里的数字.有点闪的效果还是不太好看. (Background music just casually write write array of specific numbers can be changed. Bit flash effect is still quite nice.)

P0301：数字图像矩阵数据的显示及其傅立叶变换 P0302：二维离散余弦变换的图像压缩 P0303：采用灰度变换的方法增强图像的对比度 P0304：直方图均匀化 P0305：模拟图像受高斯白噪声和椒盐噪声的影响 P0306：采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波 P0307：采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波 P0308：图像的自适应魏纳滤波 P0309：运用5种不同的梯度增强法进行图像锐化 P0310：图像的高通滤波和掩模处理 P0311：利用巴特沃斯（Butterworth）低通滤波器对受噪声干扰的图像进行平滑处理 P0312：利用巴特沃斯（Butterworth）高通滤波器对图像进行锐化处理 (P0301: digital image data matrix display and Fourier Transform P0302: two-dimensional discrete cosine transform image compression P0303: using gray transform method to enhance the contrast of the image P0304: histogram equalization P0305: Simulation images by white Gaussian noise and salt and pepper noise P0306: 2D median filtering function medfilt2 right by Salt and Pepper image noise filtering P0307: using MATLAB functions filter2 of noise images mean filtering P0308: Image Adaptive Filter Weiner P0309: use five different gradient Enhancement Act for image sharpening P0310: Images of the high-pass filtering and mask handling P0311: use Butterworth (Butterworth) low-pass filter on the noise in the image smoothing P0312: use Butterworth ( Butterworth) high-pass filter for image sharpening)

高效的文章分句算法程序,将由标点符号分开的语句的起始位置和结束位置记录到结构体里()

运用harr特征+SRC（稀疏表示）分类实现的一种车辆检测方法，文件中提供了训练和测试车辆图片。由于时间原因，所用haar特征没有优化，维度过高，导致滑窗框图过慢，本代码只输出效果统计数据，以供大家参考学习稀疏表示在车辆检测中的应用。(Using harr feature+SRC (sparse representation) classification to achieve a vehicle detection method, the paper provides a training and test vehicle picture. Due to time reasons, the use of haar feature is not optimized, high dimension, resulting in sliding sash figure is too slow, the effect of the code only output statistics for your reference learning sparse representation in the vehicle detection.)

基于置信传播的立体匹配算法，匹配精度较高(Stereo matching algorithm based on belief propagation, high matching accuracy)