Separate image of text into component character images

Question

I'd like to separate an image of text into it's component characters, also as images. For example, using the sample below I'd end up with 14 images.

I'm only going to be using text on a single line, so the y-height is unimportant - what I need to find is the beginning and end of each letter and crop to those coordinates. That way I would also avoid problems with 'i','j', etc.

I'm new to image processing, and I'm not sure how to go about it. Some form of edge detection? Is there a way to determine contiguous regions of solid colour? Any help is great.

Trying to improve my Python skills and familiarity with some of the many libraries available, so I'm using the Python Imaging Library (PIL), but I've also had a look at OpenCV.

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Sample image:

Answer 1

This is not an easy task especially if the background is not uniform. If what you have is an already binary image like the example, it is slightly simpler.

You can start applying a threshold algorithm if your image is not binary (Otsu adaptative threshold works well)

After you can use a labelling algorithm in order to identify each 'island'of pixels which forms your shapes (each character in this case).

The problem arises when you have noise. Shapes that were labelled but aren't of your interest. In this case you can use some heuristic to determine when a shape is a character or not (you can use normalized area, position of the object if your text is in a well define place etc). If this is not enough, you will need to deal with more complex staff like shape feature extraction algorithms and some sort of pattern recognition algorithm, like multilayer perceptrons.

To finish, this seems to be an easy task, but depending the quality of your image, it could get harder. The algorithms cited here can easily be found on the internet or also implemented in some libraries like OpenCv.

Any more help, just ask, if I can help of course ;)

Answer 2

I know I am few years late :-) but you can do this sort of thing with ImageMagick pretty easily now, straight at the command-line without compiling anything, as it has Connected Component Analysis built-in:

Here is one way to do it like that:

#!/bin/bash
image="$1"
draw=$(convert $image                              \
   -threshold 50%                                  \
   -define connected-components:verbose=true       \
   -define connected-components:area-threshold=10  \
   -connected-components 8                         \
   -auto-level objects.png | \
   awk 'BEGIN{command=""}
        /\+0\+0/||/id:/{next}
        {
          geom=$2
          gsub(/x/," ",geom)
          gsub(/+/," ",geom)
          split(geom,a," ")
          d=sprintf("-draw \x27rectangle %d,%d %d,%d\x27 ",a[3],a[4],a[3]+a[1],a[4]+a[2])
          command = command d
          #printf "%d,%d %d,%d\n",a[3],a[4],a[3]+a[1],a[4]+a[2]
        }
        END{print command}')

eval convert "$image" -fill none -strokewidth 2 -stroke red $draw result.png

The result looks like this:

First, I threshold your image at 50% so that there are only pure blacks and whites in it, no tonal gradations. Then I tell ImageMagick to output details of the bounding boxes it finds, and that I am not interested in objects smaller than 10 pixels of total area. I then allow pixels to be 8-connected, i.e. to their diagonal neighbours (NE,SE,NW,SW) as well as their left-right and above-below neighbours. Finally I parse the bounding box output with awk to draw in red lines around the bounding boxes.

The output of the initial command that I parse with awk looks like this:

Objects (id: bounding-box centroid area mean-color):
  0: 539x53+0+0 263.7,24.3 20030 srgba(255,255,255,1)
  11: 51x38+308+14 333.1,30.2 869 srgba(0,0,0,1)
  13: 35x39+445+14 461.7,32.8 670 srgba(0,0,0,1)
  12: 35x39+365+14 381.7,32.8 670 srgba(0,0,0,1)
  2: 30x52+48+0 60.4,27.0 634 srgba(0,0,0,1)
  1: 41x52+1+0 20.9,16.6 600 srgba(0,0,0,1)
  8: 30x39+174+14 188.3,33.1 595 srgba(0,0,0,1)
  7: 30x39+102+14 116.3,33.1 595 srgba(0,0,0,1)
  9: 30x39+230+14 244.3,33.1 595 srgba(0,0,0,1)
  10: 35x39+265+14 282.2,33.0 594 srgba(0,0,0,1)
  16: 33x37+484+15 500.2,33.0 520 srgba(0,0,0,1)
  17: 22x28+272+19 282.3,32.8 503 srgba(255,255,255,1)
  5: 18x51+424+2 432.5,27.9 389 srgba(0,0,0,1)
  6: 18x51+520+2 528.5,27.9 389 srgba(0,0,0,1)
  15: 6x37+160+15 162.5,33.0 222 srgba(0,0,0,1)
  14: 6x37+88+15 90.5,33.0 222 srgba(0,0,0,1)
  18: 22x11+372+19 382.6,24.9 187 srgba(255,255,255,1)
  19: 22x11+452+19 462.6,24.9 187 srgba(255,255,255,1)
  3: 6x8+88+0 90.5,3.5 48 srgba(0,0,0,1)
  4: 6x8+160+0 162.5,3.5 48 srgba(0,0,0,1)

and the awk turns that into this

convert http://imgur.com/AVW7A.png -fill none -strokewidth 2 -stroke red \
-draw 'rectangle 308,14 359,52'        \
-draw 'rectangle 445,14 480,53'        \
-draw 'rectangle 365,14 400,53'        \
-draw 'rectangle 48,0 78,52'           \
-draw 'rectangle 1,0 42,52'            \
-draw 'rectangle 174,14 204,53'        \
-draw 'rectangle 102,14 132,53'        \
-draw 'rectangle 230,14 260,53'        \
-draw 'rectangle 265,14 300,53'        \
-draw 'rectangle 484,15 517,52'        \
-draw 'rectangle 272,19 294,47'        \
-draw 'rectangle 424,2 442,53'         \
-draw 'rectangle 520,2 538,53'         \
-draw 'rectangle 160,15 166,52'        \
-draw 'rectangle 88,15 94,52'          \
-draw 'rectangle 372,19 394,30'        \
-draw 'rectangle 452,19 474,30'        \
-draw 'rectangle 88,0 94,8'            \
-draw 'rectangle 160,0 166,8' result.png