what I want to do is a image recognition for a simple app:

  1. given image (500 x 500) pxs ( 1 color background )
  2. the image will have only 1 geometric figure (triangle or square or smaleyface :) ) of (50x50) pxs.
  3. python will do the recognition of the figure and display what geometric figure is.

any links? any hints? any API? thxs :)


Solution 1:

A typical python tool chain would be:

  • read your images with with PIL
  • transform them into Numpy arrays
  • use Scipy's image filters (linear and rank, morphological) to implement your solution

As far differentiating the shapes, I would obtain its silhouette by looking at the shape of the background. I would then detect the number of corners using a corner detection algorithm (e.g. Harris). A triangle has 3 corners, a square 4, and a smiley none. Here's a python implementation of the Harris corner detection with Scipy.

Edit:

As you mention in the comments, the blog post didn't present the function that produces a gaussian kernel needed in the algorithm. Here's an example of a such a function from the Scipy Cookbook (great resource btw):

def gauss_kern(size, sizey=None):
    """ Returns a normalized 2D gauss kernel array for convolutions """
        size = int(size)
        if not sizey:
            sizey = size
        else:
            sizey = int(sizey)
        x, y = mgrid[-size:size+1, -sizey:sizey+1]
        g = exp(-(x**2/float(size)+y**2/float(sizey)))
        return g / g.sum()

Solution 2:

OpenCV has blob analysis tools, it will give you metrics about the shape which you can feed for your favourite pattern recognition algorithm :) Eg. rectangle has 1.0 ratio for area / (height * width), when circle's ratio is about 0.78.