41
votes

I'm currently building what basically amounts to a cross between a search engine and a gallery for web comics that's focused on citing sources and giving authors credit.

I'm trying to figure out a way to search an image to find characters within it.

For example:

cyanide and happiness

Assuming I have the red character and the green character saved as Red Man and Green Man how do I determine if an image contains one or the other.

This doesn't need to have 100% recognition or anything is this is more of an added feature I'd like to create, I'm just not sure where to start. I've done a lot of googling for image recognition but haven't found much helpful.

For what it's worth, I'd prefer to do this using Python.

3
Take a look at sikuli script - JBernardo
I don't see how sikuli would be used for this. Sikuli looks like it's strictly for GUI interfaces. These are user uploaded pictures on a web server. - Adam
Sikuli is not only for GUI's. You can technically use it to run any Jython script you want. You could write a script that would open the user images then look for the image pattern you want to find. That's just a first blush idea. - Snaxib
However, Sikuli doesn't support scaling or rotation in images.... - Adam

3 Answers

54
votes

For anyone who stumbles across this in the future.

This can be done with template matching. To summarize (my understanding), template matching looks for an exact match of one image within another image.

Here's an example of how to do it within Python:

import cv2

method = cv2.TM_SQDIFF_NORMED

# Read the images from the file
small_image = cv2.imread('small_image.png')
large_image = cv2.imread('large_image.jpeg')

result = cv2.matchTemplate(small_image, large_image, method)

# We want the minimum squared difference
mn,_,mnLoc,_ = cv2.minMaxLoc(result)

# Draw the rectangle:
# Extract the coordinates of our best match
MPx,MPy = mnLoc

# Step 2: Get the size of the template. This is the same size as the match.
trows,tcols = small_image.shape[:2]

# Step 3: Draw the rectangle on large_image
cv2.rectangle(large_image, (MPx,MPy),(MPx+tcols,MPy+trows),(0,0,255),2)

# Display the original image with the rectangle around the match.
cv2.imshow('output',large_image)

# The image is only displayed if we call this
cv2.waitKey(0)
42
votes

As Moshe's answer only covers matching a template that is contained only once in the given picture. Here's how matching several at once:

import cv2
import numpy as np

img_rgb = cv2.imread('mario.png')
template = cv2.imread('mario_coin.png')
w, h = template.shape[:-1]

res = cv2.matchTemplate(img_rgb, template, cv2.TM_CCOEFF_NORMED)
threshold = .8
loc = np.where(res >= threshold)
for pt in zip(*loc[::-1]):  # Switch collumns and rows
    cv2.rectangle(img_rgb, pt, (pt[0] + w, pt[1] + h), (0, 0, 255), 2)

cv2.imwrite('result.png', img_rgb)

(Note: I changed and fixed a few 'mistakes' that were in the original code)

Result:

detect mario coins (before/after)

Source: https://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_imgproc/py_template_matching/py_template_matching.html

1
votes

OpenCV has a Python interface that you could look at. If the characters, don't change too much you could try to use the matchTemplate function.

Here is their official tutorial on it (the tutorial is written using the C++ interface, but you should be able to get a good idea of how to use the function in Python from it).