imageMosaic

一种新的改进的LBP特征提取方法，采用多块比较的方法(a new LBP feature extraction method)

数字图像处理中的几何变换，包括图像的平移，图像的镜像，图像转置，图像的缩放，图像的旋转以及三种插值算法(The geometric transformation in digital image processing includes image translation, image mirroring, image transposition, image scaling, image rotation, and three interpolation algorithms)

为了提高数字图像中椭圆检测的效率和准确性,提出了一个基于最小二乘法的改进的随机椭圆检测算法. 该算法随机选取图像中的3 个边缘点,在以这3 个点为中心的窗口内,从边缘点中拟合出可能椭圆,并通过随机选 取的第4 个边缘点来确认可能椭圆. 利用直接最小二乘法椭圆拟合的特性,引入可能椭圆边缘点收集和椭圆重新 拟合的迭代过程来提取最终的椭圆参数. 通过对含有不同噪声的仿真图片和包括残缺椭圆的实际图片的实验表 明,新算法的改进是有效的. 与原算法相比,新算法降低了对参数的依赖性,提高了检测的速度、稳定性和准确性, 同时保留了原算法的抗噪声能力.(: An imp roved randomized ellip se detection algorit hm based on least square approach was proposed to enhance t he efficiency and accuracy of ellip se detection in digital images. This algorit hm randomly se2 lect s three edge point s in t he image , and t hen uses least square approach to fit all t he edge point s in three windows , which are defined by t he t hree edge point s. The forth edge point is randomly selected to judge whet her a possible ellip se exist s in t he image. Utilizing the characteristic of direct least square fit ting of ellip se , an iteration process of edge point collecting and ellip se refit ting of possible ellip se was int roduced to ext ract t he final ellip se’s parameters. Artificial images wit h different level s of noise and nature images containing incomplete ellip ses were employed to test t his algorithm. Experimental result s show that t he improvement s are notable. Compared with the original algorit hm , t he propo sed algorit hm reduces)

基于Gabor的特征提取,gabor滤波器的构造 包含中科院的虹膜库(base on gabor zhongkeyuandehongmoku)

动目标检测，包括动目标检测理论，动目标检测器，目标检测公式(Moving target detection, including moving target detection theory, moving object detection, object detection formula)

图像处理入门教程，比较适合初学者，对于图像知识有所掌控，内容比较详细。(Image Processing Getting Started tutorial, suitable for beginners, more detailed image of knowledge has been the control.)

实现图像文件（如bmp等）的读取、显示、真彩图转换成灰度图、灰度图转化为二值图及绘制图像直方图功能。(Achieve an image file (such as bmp, etc.) to read, display, true color conversion to grayscale, converted to grayscale and binary image histogram function to draw the image.)

视频演示算法包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (Algorithm for video presentation include: 1. Static background background prediction target detection 2. Static background frame difference method for target detection 3. Mean Shift tracking method 4. Gravity multi-target tracking method)

Perona-Malik的线性和非线性融合多尺度提边算法代码(Perona-Malik of the linear and nonlinear fusion algorithm for multi-scale edge mention code)

SIFT 尺度不变特征提取算法 可参考可运行有测试图片(SIFT with test picture and it can work well)