在opencv-python中檢測星形

我需要檢測形狀並計算圖像中每個形狀的發生次數。我最初檢測輪廓並近似它們，並計算出每個輪廓中的頂點。我的代碼看起來像像這樣：在opencv-python中檢測星形

import cv2 
import numpy as np 
import collections 
import sys 

img = cv2.imread(str(sys.argv[1]),0) 
ret,thresh = cv2.threshold(img,127,255,0) 
contours,hierarchy = cv2.findContours(thresh,1,2) 


no_of_vertices = [] 

i = 0 
mask = np.zeros(img.shape,np.uint8) 
for contour in contours: 

cnt = contour 
area = cv2.contourArea(cnt) 
if area>150: 
    epsilon = 0.02*cv2.arcLength(cnt,True) 
    approx = cv2.approxPolyDP(cnt,epsilon,True) 
    no_of_vertices.append(len(approx)) 



counter = collections.Counter(no_of_vertices) 




a,b = counter.keys(),counter.values() 

i=0 
while i<len(counter): 
    print a[i],b[i] 
    i = i + 1

此圖像中檢測到的星星我的代碼does not工作：

我應該做的代碼什麼樣的變化？

來源

2015-12-10 Kaushik Ramachandran

from（dense或sparse）contour，try matc hShape函數：http://docs.opencv.org/2.4/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html#double%20matchShapes%28InputArray%20contour1,%20InputArray%20contour2,%20int%20method,%20double%20parameter%29 – Micka

您可以使用_circularity_來檢測形狀：'（4 * pi * area）/（perimeter^2）'。星形的圓度大約爲0.25，例如 – Miki

對我而言，有效的方法是比較形狀周邊區域的平方根。大約0.145（+/- 0.0015，因爲一些邊緣沒有完美呈現）。六角形爲0.255，三角形爲0.21，方形爲.247，五角形爲.250。圓形度也起作用（其中三角形的進入角度爲0.26到0.27），並且它也有類似的區別（三角形的.83爲三角形的.55-.56，方形的爲0.77， 78五角大樓）

下面是它的C++代碼（我沒有在這裏我的電腦上蟒蛇，但這個想法是一樣的）：

#include "stdafx.h" 
#include <opencv/cxcore.h> 
#include <opencv2\core\mat.hpp> 
#include <opencv2/highgui/highgui.hpp> 
#include <iostream> 
#include <opencv/cxcore.h> 
#include <opencv/highgui.h> 
#include <opencv/cv.h> 
#include <opencv2/opencv.hpp> 
#include <opencv2/core/core.hpp> 

using namespace cv; 
using namespace std; 

RNG rngee(12345); 

int main() { 
    Mat im = imread("C:/this/is.a/path/image.png", CV_LOAD_IMAGE_COLOR); 
    Mat imgrey = im.clone(); 
    cvtColor(im, imgrey, CV_RGB2GRAY); 
    vector<vector<Point> > imContours; 
    vector<Vec4i> hierarchy; 

    double divMaxSize = 0.175, divMinSize = 0.125; 

    namedWindow("Image", CV_WINDOW_NORMAL| CV_WINDOW_KEEPRATIO | CV_GUI_EXPANDED); 

    threshold(imgrey, imgrey, 100, 255, 0); 

    findContours(imgrey, imContours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0)); 

    for (int i=0; i < imContours.size(); i++) { 
     Scalar color = Scalar(rngee.uniform(0, 255), rngee.uniform(0,255), rngee.uniform(0,255)); 
     cout << "sqrt(Area)/arcLength = " << sqrt(contourArea(imContours[i]))/arcLength(imContours[i], true) << endl; 
     if(sqrt(contourArea(imContours[i]))/arcLength(imContours[i], true) < divMaxSize && sqrt(contourArea(imContours[i]))/arcLength(imContours[i], true) > divMinSize) 
     { 
      drawContours(im, imContours, i, color, 2, 8, hierarchy, 0, Point()); 
      cout << "I'm a star!" << endl; 
     } 
     imshow("Image", im); 
     waitKey(0); 
    } 
    imshow("Image", im); 
    waitKey(0); 

}

兩種方式 - 無論是使用圓或我的sqrt（area）/ arclength method - results in： image with stars highlighted

來源

2015-12-11 19:37:49

非常感謝！它幫助:) –

在opencv-python中檢測星形

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