Question

So my problem is a relatively simple one, but still quite hard for a Python rookie like me.
So I essentially have a number of shapes in an input image like a bunch of small triangles in a square or so. I need to extract the outer square and each triangle from within the image. I’ve developed a simple template matching code to do this… but it does not seem to work!

while ( len(numpy.where( b <150 )[0])!=xx):
xx=len(numpy.where( b <150 )[0])
for v in range(len(b)-len(a)):
    for w in range(len(b[0])-len(a[0])):
        c=b[v:v+len(a[0]),w:w+len(a)]
        c.flags.writeable=False
        #c=b.reshape(len(a),len(a))
        vv=sum(sum(c-a))
        #print v, w
        if(vv<minval):
            minval=vv
            xcor=v
            ycor=w

print xcor, ycor, minval
print len(numpy.where( b <150 )[0])
print b[xcor:xcor+len(a),ycor:ycor+len(a[0])]
for p in range(xcor,xcor+len(a)):
    for q in range(ycor,ycor+len(a[0])):
        b.setflags(write=True)
        b[p][q]=251;
#print b[xcor:xcor+len(a),ycor:ycor+len(a[0])]
xcorr=0
ycorr=0
minval=99999

The problem is that I need to extract only a simple set of figures, but my code goes on and on… Also, I do not know how to handle the TRIANGLES IN A BOX problem. Can someone please help me out?

By extract, I mean only find out just where the object is placed… if it is placed at all!

Answer 1

If you decide to use opencv, this should get you started:

import cv2

def show_image_and_wait_for_key( image, name="Image" ):
    print "showing",name,"(waiting for input)"
    cv2.imshow('norm',image)
    cv2.waitKey(0)

def draw_segments( image , segments, color=(255,0,0), line_width=1):
        '''draws segments on image'''
        for segment in segments:
            x,y,w,h= segment
            cv2.rectangle(image,(x,y),(x+w,y+h),color,line_width)

original= cv2.imread("ravens.jpg")
image=original
image= cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
image= cv2.GaussianBlur(image,(3,3),0)
_, image= cv2.threshold( image, 140, 255, cv2.THRESH_BINARY )
contours,hierarchy = cv2.findContours(image.copy(),cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
segments= [cv2.boundingRect(c) for c in contours] 
draw_segments( original, segments )
show_image_and_wait_for_key( original )

After this, you can filter by rectangle area, position, aspect ratio, etc.
You can extract a region from the image using this function:

def region_from_segment( image, segment ):
    '''given a segment (rectangle) and an image, returns it's corresponding subimage'''
    x,y,w,h= segment
    return image[y:y+h,x:x+w]

All images are also numpy ndarray, so you should be comfortable with the cv2 interface