try to implement halcon shape based matching, refer to machine vision algorithms and applications, page 317 3.11.5, written by halcon engineers https://github.com/meiqua/shape_based_matching++https://www.zhihu.com/people/mei-qu-a https://github.com/daxiaHuang/shape_based_matching_subpixel htt...
1080 0 00:17 App opencv c++ 轮廓匹配 2850 0 00:20 App opencv 卡尺法 采集边缘点 拟合直线 362 0 01:49 App 基于边缘梯度方向的模板匹配 shape based matching 9040 0 01:49 App Qt+openCV测量多边形各边长度及轮廓总长度 浏览方式(推荐使用) 哔哩哔哩 你感兴趣的视频都在B站 打开信息...
1、使用程序自带图片进行roi裁剪 2、将 std::vector<int> T; T.push_back(4); T.push_back(8); line2Dup::Detector detector(50, T); 特征数量改为50 3、打开vs的openMP支持 没有其他任何改动,最后的匹配时间为,基本都在122ms左右。这个时间应该不对吧 Owner meiqua commented Nov 14, 2019 vs需要...
/*M/// // // Author : KayChan // Explain : Shape matching // //M*/ #ifndef _KCG_MATCH_H_ #define _KCG_MATCH_H_ #include <opencv2/opencv.hpp> #include <omp.h> #ifndef ATTR_ALIGN # if defined(__GNUC__) # define ATTR_ALIGN(n) __attribute__((aligned(n))) # else #...
Template matching: opencv's matchTemplate The simplest solution is to find the most suitable target by panning the template in the target image Contour: HALCON Shape-based Matching, Canny I haven't used it, I can't write it, the halcon will cost money ...
shape. 形状距离和匹配 signal. 信号处理 stereo. 立体匹配算法 structured_light. 结构光 API superres. 超分辨率 surface_matching. 表面匹配 text. 场景文本检测和识别 tracking. 跟踪 API videostab. 视频稳定 viz. 3D 可视化工具 wechat_qrcode. 用于检测和解析二维码的微信二维码检测器 ...
opencv_shapeshape matching, rare uses on mobile, build the source externally if you need opencv_stitchingimage stitching, rare uses on mobile, build the source externally if you need opencv_superresdo video super-resolution on powerful pc or server ...
shape (Shape Distance and Matching 形状距离与匹配) 仿射变换、基于Chi、EMD、EMD-L1、norm cost提取、形状距离、形状内容描述和匹配算法 stereo (Stereo Correspondance Algorithms 立体匹配算法) Quasi、BM、SGBM立体匹配、视差图去噪 structured_light(Structured Light API 结构光API) ...
mask = np.zeros(gray_image.shape[:2], np.uint8) mask[30:190, 30:190] = 255 因此,遮罩由尺寸与加载的图像相同的黑色图像组成,而白色的图像对应于我们要计算直方图的区域。然后,通过创建的掩码调用cv2.calcHist()函数:hist_mask = cv2.calcHist([gray_image], [0], mask, [256], [0, 256]) ...
# Create the SIFT detector.sift = cv2.xfeatures2d.SIFT_create()# Perform SIFT feature detection and description on the# query image.query_kp, query_ds = sift.detectAndCompute(query,None)# Define FLANN-based matching parameters.FLANN_INDEX_KDTREE =1index_params =dict(algorithm=FLANN_INDEX_KD...