http://www.iotword.com/3113.html WebHarris算法实现代码: #encoding:utf-8 from pylab import * from PIL import Image from PCV.localdescriptors import harris from PCV.tools.imtools import imresize """ This is the Harris point matching example in Figure 2-2.
【Opencv】基于Opencv和PCV两种方法的Harris 角点检测 …
WebWindows cmd PCV cd PCV python setup.py install PCV PCV Python Shell Shell f import PCV PCV 0.4 VLfeat VLFeat SIFT, MSER, HOG, K- MEANS, Hierarchical K-means sift VLfeat VLFeat, 32 win32 VLFeat 0.9.18 0.9.18 0.9.17 bin win32 “bin” "win32vlfeat" PCV f sift.py def process_image (imagename,resultname,params="‐‐edge‐thresh 10 … Webprint ('starting matching') matches = harris.match_twosided(d1, d2) figure() gray() harris.plot_matches(im1, im2, filtered_coords1, filtered_coords2, matches) show() 2、SIFT(尺度不变特征变换) from PIL import Image from pylab import * import sys from PCV.localdescriptors import sift brophy metal products
计算机视觉python--Harris角点检测
Web# -*- coding: utf-8 -*-from PIL import Image from pylab import * from PCV. localdescriptors import sift from PCV. localdescriptors import harris # ... sift 的特征 … Web答案是Harris算法。 Harris算法使用微分运算和自相关矩阵来进行角点检测,具有运算简单、提取的角点特征均匀合理、性能稳定等特点。 假设图像像素点(x,y)的灰度为 I(x,y),以像素点为中心的窗口沿 x 和 y 方向分别移动 u 和 v 的灰度强度变化的表达式为: Webfrom pylab import * from PIL import Image from PCV. localdescriptors import harris from PCV. tools. imtools import imresize """ This is the Harris point matching example in Figure 2-2. """ # Figure 2-2上面的图 #im1 = array (Image.open ("../data/crans_1_small.jpg").convert ("L")) #im2 = array (Image.open … care products shower gurney