im_dilate

利用c均值方法对图象进行聚类分割,此为matlab环境下的仿真代码(Use c-means clustering methods for image segmentation, this is matlab code simulation environment)

有详实的说明，基于C-V模型的图像分割，属于活动轮廓模型，有典型的图片例子，可以直接运行，适合研究生使用。(There are detailed instructions, CV model-based image segmentation, are active contour models, with typical picture examples can be run directly, for graduate students to use.)

利用正交匹配跟踪原子库对信号进行稀疏分解程序(Using orthogonal matching pursuit atom libraries for signal sparse decomposition process)

车辆检测，车辆识别，对输入的车辆图像进行识别并输出识别结果(Vehicle detection, vehicle recognition, recognition of input vehicle images and output of recognition results.)

并行磁共振成算法GRAPPA，希望对大家有帮助，内有K空间数据。(Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA))

图像逆透视变换的示例，用于合成360度全景俯视图。(An example realizes the image processing of Inverse Perspective Mapping, which is used in composing 360 panorama planform.)

SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。 该方法于 1999 年由 David Lowe 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004 年再次经 David Lowe 整理完善后发表于 International journal of computer vision（IJCV） 。截止 2014 年 8 月，该论文单篇被引次数达 25000 余次。(来自百度)(SIFT, namely Scale-invariant feature transform (SIFT), is a description used in the field of image processing. This description has scale invariance and can detect key points in images. It is a local feature descriptor. This method was first published by David Lowe at the International Conference on Computer Vision (ICCV) in 1999 and published in the International Journal of Computer Vision (IJCV) in 2004 after it was sorted out and perfected by David Lowe again. As of August 2014, more than 25,000 citations have been cited. (From Baidu))

小波去噪,实现阈值小波去噪，并且含有frost去噪，并且输出信噪比(Wavelet denoising, to achieve the threshold wavelet denoising, denoising and contains frost, and the output signal to noise ratio)

基于SIFT+Kmeans+LDA的图片分类器的实现源码。 博文参考：http://www.cnblogs.com/freedomshe/archive/2012/04/24/2468747.html(The pictures classifier based on SIFT, Kmeans and LDA. Blog Reference: http://www.cnblogs.com/freedomshe/archive/2012/04/24/2468747.html)

基于颜色来检测火焰，将是频频分帧，然后逐帧检测，碧昂切将火焰全画出来，基础编程。(Based on color to test the flame, basic programming )