Mybole

说明：  用canny算子来检测图像边缘，VC++(Using canny operator to detect image edge)

FIR滤波器的C语言实现 C语言源程序代码及解析(FIR filter, the C language realization C source code and analytical)

CT模型仿真，里面有C还有Matlab文件，均可以使用(CT model simulation with C and Matlab)

Abstract—Noninvasive ultrasound imaging of carotid plaques allows for the development of plaque-image analysis methods associated with the risk of stroke. This paper presents several plaqueimage analysis methods that have been developed over the past years. The paper begins with a review of clinical methods for visual classification that have led to standardized methods for image acquisition, describes methods for image segmentation and denoizing, and provides an overview of the several texture-feature extraction and classification methods that have been applied. We provide a summary of emerging trends in 3-D imaging methods and plaque-motion analysis. Finally, we provide a discussion of the emerging trends and future directions in our concluding remarks.

改进经典的otsu算法，使其适应目标所占图像比例较小的情况，使图像分割方法更具有自适应性 (Improve classic otsu algorithm to achieve image segmentation)

小波算法。机械化的提高我们的效率。让我们减少错误率。大家要对她有性心。(Wavelet algorithm. Mechanization to improve our efficiency. Let us reduce the error rate. We have to have sex to her heart.)

这是一个比较完整的KPCA算法，通过这个算法可以快速的找到主要的特征向量进行主成分分析。(This is a relatively complete KPCA algorithm, this algorithm can quickly find the main feature vector principal component analysis.)

：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)

给图像加椒盐和高斯噪声，以及空域滤波（中值和均值滤波）！(to Image pretzels and Gaussian noise, and the spatial filter (mean values and filter)!)

opencv读取一个视频并设置其播放帧率播放速度(use opencv to read a video and change the rate)