2006011437_HW_2

对图形进行二维傅里叶变化后的频谱进行中心化(Centralization of the spectrum after two-dimensional Fourier transform)

基于VisualC_和DCMTK的医学DICOM图像显示与调窗,同时在MFC 下完成鼠标拖动进行窗宽/窗位的调节(Medical image of DICOM VisualC_ and DCMTK display and window based on, at the same time in MFC complete the mouse to drag the window width/window regulator )

说明：  这是基于Camshift的目标跟踪code，编程语言为matlab。下载解压后可以直接运行。(This is the target tracking code based on CAMSHIFT, and the programming language is matlab. After downloading and decompressing, you can run it directly.)

语音特征提取代码，提取mfcc和lpcc。(Speech feature extraction code, and extract mfcc lpcc.)

说明：  用matlab实现汽车牌照识别系统的定位算法(Automobile License Plate Recognition System Location Algorithm)

传统的图像分割方法可以分为基于阈值、边缘、区域的方法等，而传统的分割方法在复杂图像分割中效果不好。为了提高图像分割的性能，我们提出了一种基于局部自适应窗口的Otsu方法。首先，分析了传统阈值法在复杂图像分割中不能很好地形成的原因，比较了全局阈值和局部阈值对图像分割的影响。其次，提出了根据局部信息自适应地改变局部窗口大小的方法，分析了该方法的特点。最后，证明了所提出的新方法优于其他方法。实验结果表明，与其他传统方法相比，该方法能保持更多的细节，获得更满意的结果。(The traditional image segmentation methods can be divided into thresholding, edge and region methods. The traditional segmentation methods do not perform well in the segmentation of complicated images. In order to improve the performance of image segmentation, we propose an adaptive windowed range-constrained Otsu method based on local information.First, the reason why traditional thresholding methods do not perform well in the segmentation of complicated images is analyzed. Therein, the influences of global and local thresholdings on the image segmentation are compared. Secondly, a method of adaptively changing the local window size based on local information is proposed, and the characteristics of the proposed method are analyzed. Finally, the superiority of the proposed method over other methods, It is validated by the experiments that the proposed method can keep more details and acquire much more satisfying results as compared with the other conventional methods.)

以多光谱数据为原始数据，通过空间变换、滤波、融合、纹理及图像处理等手段，提取遥感图像多维、多尺度特征，最终建立面向目标检测、识别和分析的特征空间，并使用NASA的实测数据对方法的性能进行验证和分析。(Multi-spectral data to the original data, through space conversion, filtering tools, integration, texture and image processing, remote sensing images to extract multi-dimensional, multi-scale features, for the eventual establishment of target detection, identification and analysis of the characteristics of the space, and measured using NASA performance of the method for data verification and analysis.)

图像处理中的数学修炼

阴影去除，用于视频监控中的运动目标检测后提取运动目标(Shadow Removal for moving object detection in video surveillance Moving Target Extraction)

Mean shift and other image segmentation algorithms.