SketchCommonCVPR10_v1.1.tar.gz.tar

图像阈值化分割,图像阈值化分割,图像阈值化分割(Image thresholding segmentation.Image thresholding segmentation.Image thresholding segmentation)

基于MRF模型的变化检测算法仿真 MRF建模用于SAR去噪，再通过EM算法实现变化检测(MRF model-based change detection algorithm simulation)

利用matlab提取掌纹图像的感兴趣区域，ROI提取(Extract palmprint images using matlab region of interest, ROI extraction)

静态图片转化为动态图片，把静态的图片转化为动态的(convert PNG picture to GIF picture)

快速将图片裁剪为电脑壁纸和ipad壁纸尺寸，带预览(To cut pictures as PC or Ipad size conveniently)

Invensense公司的modm实例代码example。 初始化以及IIC的引用示例。(The example of modm from Invensense. IIC initiation and configuration initiation.)

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)

毕业设计，基于内容的图像检索，支持的检索特征包括 sift,颜色直方图，灰度矩阵，HU不变矩，边缘方向直方图，检索方法使用K-means和K-D树两种，需要OPENCV支持，运行时请先选定一个文件夹来生成特征库，特征库用access数据库保存，只支持JPG文件(Graduate design, content-based image retrieval, search features, including support sift, color histogram, gray matrix, HU moment invariants, edge direction histogram, retrieval method using the K-means and KD trees are two kinds of needs OPENCV support Please select a runtime folder to generate the feature library, feature library with access database save, only supports JPG files)

直方图调整并显示对比，直方图调整后都需要对比一下调整前与调整后的区别，并显示。此程序适合初学者学习。(Histogram and adjust the display contrast)

灰度图像的属性计算：利用bwlabel和regionprops函数对度量二值图像中目标对象的属性。(Attribute gray image: Using bwlabel and regionprops function measure binary image of the target object attributes.)