If you have only these regular shapes, there is a simple procedure as follows :
- Find Contours in the image ( image should be binary as given in your question)
- Approximate each contour using
approxPolyDP
function. - First, check number of elements in the approximated contours of all the shapes. It is to recognize the shape. For eg, square will have 4, pentagon will have 5. Circles will have more, i don’t know, so we find it. ( I got 16 for circle and 9 for half-circle.)
- Now assign the color, run the code for your test image, check its number, fill it with corresponding colors.
Below is my example in Python:
import numpy as np import cv2 img = cv2.imread('shapes.png') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) ret,thresh = cv2.threshold(gray,127,255,1) contours,h = cv2.findContours(thresh,1,2) for cnt in contours: approx = cv2.approxPolyDP(cnt,0.01*cv2.arcLength(cnt,True),True) print len(approx) if len(approx)==5: print "pentagon" cv2.drawContours(img,[cnt],0,255,-1) elif len(approx)==3: print "triangle" cv2.drawContours(img,[cnt],0,(0,255,0),-1) elif len(approx)==4: print "square" cv2.drawContours(img,[cnt],0,(0,0,255),-1) elif len(approx) == 9: print "half-circle" cv2.drawContours(img,[cnt],0,(255,255,0),-1) elif len(approx) > 15: print "circle" cv2.drawContours(img,[cnt],0,(0,255,255),-1) cv2.imshow('img',img) cv2.waitKey(0) cv2.destroyAllWindows()
Below is the output:
Remember, it works only for regular shapes.
Alternatively to find circles, you can use houghcircles
. You can find a tutorial here.
Regarding iOS, OpenCV devs are developing some iOS samples this summer, So visit their site : www.code.opencv.org and contact them.
You can find slides of their tutorial here : http://code.opencv.org/svn/gsoc2012/ios/trunk/doc/CVPR2012_OpenCV4IOS_Tutorial.pdf