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200707171150141339
- 这个Matlab程序实现一个基于活动轮廓的边缘检测，而不进行重新初始化。-The Matlab program of active contour based on edge detection, rather than re-initialization.
Extractionofedgedetectionandcontourfollowing
- 边缘检测提取及轮廓跟踪及一些化码，很有用的，你一定用得上。-Extraction of edge detection and contour following and some of code, very useful, you will need them.
contours
- 在VS2008环境下基于OpenCV画出图片中的轮廓，用到Canny算子边缘检测、形态学变换和轮廓遍历-VS2008 environment based on OpenCV draw the outline of the picture, used Canny operator edge detection, morphological transformation and contour traversal
TrackandID
- 在vc++6.0下，利用opencv函数库，使用轮廓检测法检测车辆，并显示实现车辆的跟踪和计数-Use opencv library in vc++6.0, using contour detection assay vehicle and display of vehicle tracking and counting
P0802
- 自已写的粘连字切割算法，轮廓检测,凸检测-Adhesions write their own words cut algorithm, contour detection, convex detection
Contour-Detection
- piano contpue detection - image processing
The-pedestrian-contour-detection
- 可以完整的进行行人轮廓的检测及背景提取和分析-Can complete pedestrian contour detection and background extraction and analysis
Background
- 基于背景的目标检测，是全面的MATLAB代码，运动视觉中目标的精确提取与跟踪算法，包括运动检测、阴影消除、外轮廓提 取以及目标的跟踪四个方面。-Background target detection based on MATLAB code, is comprehensive, accurate extraction and target tracking algorithm for visual motion in four aspects, including motion detectio
contour
- 车道线检测,用的是OPENCV对道路的车道线进行识别处理。-Lane detection, using a OPENCV lane road to recognition processing.
GeoMatch_demo
- 一个比较简单的基于轮廓的物体检测程序。适合初学者了解学习。-A relatively simple contour based object detection program. Suitable for beginners to learn.
stomach-cancer-(b)
- This the source code for stomachcancer detection using active contour segmentation and SVM classification method-This is the source code for stomachcancer detection using active contour segmentation and SVM classification method
Freeman
- Freeman链码圆检测，精确检测圆的轮廓-Freeman chain code detection, accurate detection of circular contour
contour
- pre-processing image -smoothing image -histogram normalization edge detection -canny edge detection draw contours
vedio
- 目标检测与识别 1. 颜色检测 采集大量敌方机器人的图片数据，并进行训练，得到对方机器人的颜色区间， 并以此为阈值对整幅图像进行颜色检测，找到疑似敌方机器人的区域，量化 成二值图。 2. 滤除噪声点 对得到的二值图像进行开运算处理，滤除颜色检测结果中的噪声点。 3. 连通区域检测 对图像中的疑似区域进行连通区域检测，计算出每个疑似区域的外部轮廓， 用矩形近似表示。 4. 连通区域合并 根据连通区域之间的距离和颜色相似性，将距离接近且相似性高的连通区域
r
- 数字图像二值化，canny边缘检测并提取轮廓进行椭圆拟合找出质心点(Two values of digital image, Canny edge detection and extraction of contour by ellipse fitting to find the centroid point)
simulate
- 形状是由图像的轮廓形成的，所以理论上形状识别是通常在边缘或轮廓检测后的步骤。(edge_based_matching The shape is formed by the outline of the image, so theoretically the shape recognition is usually the step after the edge or contour detection)