资源列表
opencvsift
- SIFT 算法提取图像局部特征， 成功应用于物体识别、图像检索等领域。SIFT 算法主要分为四个步骤： 检测尺度空间极值点、精确定位极值点、为每个关键点指定方向参数、关键点描述子的生成。-SIFT algorithm to extract local image features, successfully applied to object recognition, image retrieval and other fields. SIFT algorithm is divided into
Kalman-filter-sample-code
- 目标图像跟踪-Object tracking
123MNISTTrain
- 手写数字训练识别，基于MNIST库进行训练识别，6W个训练样本，识别率95 以上-Handwritten numeral recognition training, training on MNIST library identification, 6W training samples, the recognition rate of 95 or more
CV2_Learn_ContentFinder
- 使用opencv2写的，利用均值漂移（Mean Shift）算法查找感兴趣的物体。-Use opencv2 write, using mean shift (Mean Shift) algorithm to find the object of interest.
CV2_Learn_MorpFeature
- 使用opencv2写的，使用形态学滤波对图像进行边缘及角点的检测。-Use opencv2 write, using morphological filtering the image edge and corner detection.
CV2_Learn_LineFinder
- 使用opencv2写的，利用概率霍夫变换检测直线，并检测带有端点的线段。-Use opencv2 written using probabilistic Hough transform to detect straight line, and the line segment with endpoint detection.
CV2_Learn_Harris
- 使用opencv2写的，检测Harris角点。-Use opencv2 write, Harris corner detection.
CV2_Learn_CameraCalibrator
- 使用opencv2写的，估计相机参数，进行相机标定。-Use opencv2 written estimate camera parameters for camera calibration.
MOTIONTEST(opencv)
- 目前发现最好的一个移动目标检测，同时已经转换为VS2010项目，并成功测试，用USB摄像头，检测移动物体，基于opencv-Discover the best one currently moving target detection, and has been converted to a VS2010 project and successfully tested with USB camera to detect moving objects, based on opencv
opencv
- Opencv 2.4最新的 API,帮助您快速掌握opencv-Opencv 2.4 latest API,help you familar with opencv
opencv_extration
- 配置好opencv库以后，对图片中某个区域提取出来单独进行处理，处理完毕后放回原图像。-After configuring the opencv library, an area on the image is processed separately extracted, processed back into the original image after.
opencv-relex-detection-
- 对槽内多边形区域是否松动出槽外的松动检测，本程序运用harris角点检测的方法进行处理，-Polygonal area is loose on the tank outside the groove loose detection, the use of this program harris corner detection method for processing,