人脸识别系统设计—毕业设计

使用光流法对运动目标进行估计，要使用opencv一起实现。效果还不错(Using optical flow method to estimate the moving target, to use opencv implemented together. Results were pretty good)

实现图像的平移 可实现左移 右移 并根据需要改变参数(Image translation)

图像匹配，可以实现目标图像的匹配，匹配出最相似的训练图片。(Image matching, the matching can achieve the target image, matching the most similar training images.)

bmp文件的读取,2,8,16,24bit自适配(bmp file read,2、8、16、24bit adjust)

利用OpenCV实现单幅图片对于手指的精确识别(Single image using OpenCV to achieve precise identification of the finger)

该类计算图像的主分量,特征值,特征向量,并且使用主分量重构.(The main components of such calculation of the image, feature values, feature vectors, and the use of principal component reconstruction.)

三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准 效率较低，提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准，获得较好 的点云初始位置，然后在经典 ICP 算法的基础上，采用 k － d tree 结构实现加速搜索，并利用方向向量夹角阈值去除 错误点对，提高算法的效率。实验表明，本算法流程在保证配准精度的前提下，显著提高了配准效率。 (Three-dimensional laser point cloud registration is one of the key three-dimensional point cloud model. High classical ICP algorithm to the initial position of the point cloud registration requirements and low efficiency, proposed an improved ICP point cloud registration algorithm. Firstly, the use of principal component analysis of the initial point cloud registration, get a better initial position of the point cloud, then the basis of classical ICP algorithm using k- d tree structure to achieve speed up the search, and using the direction vector angle the removal of the threshold point error and improve the efficiency of the algorithm. Experiments show that the algorithm processes to ensure the accuracy of registration under the premise, significantly improve the efficiency of registration.)

硕士学位论文:在高分辨率成像声纳系统和回波测深仪的两个控制平台的基础上对声纳图像数据的高速显示技术的研究。文中所有的程序编写都是使用C和C++语言，在WindowsXP平台下利用VC++6．0进行编译和调试的。(study for high speed display technology on sonar image data)

图像拼接源码实现，包括多频率图像融合，sift特征点配准算法(Image Stitching source implementation, including multi-frequency image fusion, sift feature points matching algorithm)

canny边缘检测，还有车道线检测。效果还可以。(canny edge detection, and lane detection. The effect can be.)