python - Extracting code from photograph of T-shirt via OCR

Question

I recently saw someone with a T-shirt with some Perl code on the back. I took a photograph of it and cropped out the code:

Next I tried to extract the code from the image via OCR, so I installed Tesseract OCR and the Python bindings for it, pytesser.

Pytesser only works on TIFF images, so I converted the image in Gimp and entered the following code (Ubuntu 9.10):

>>> from pytesser import *
>>> image = Image.open('code.tif')
>>> print image_to_string(image)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "pytesser.py", line 30, in image_to_string
    util.image_to_scratch(im, scratch_image_name)
  File "util.py", line 7, in image_to_scratch
    im.save(scratch_image_name, dpi=(200,200))
  File "/usr/lib/python2.6/dist-packages/PIL/Image.py", line 1406, in save
    save_handler(self, fp, filename)
  File "/usr/lib/python2.6/dist-packages/PIL/BmpImagePlugin.py", line 197, in _save
    raise IOError("cannot write mode %s as BMP" % im.mode)
IOError: cannot write mode RGBA as BMP
>>> r,g,b,a = image.split()
>>> img = Image.merge("RGB", (r,g,b))
>>> print image_to_string(img)
Tesseract Open Source OCR Engine

     éi     _   l_` _ t  
  ’   ‘" fY`  
  {  W       IKQW
  ·  __·_  ‘ ·-?·      
       :W   Z  
  ··  I  A n   1   
           ;f        
     `    `      
`T     .' V   _ ‘  
I  {Z.; ? ;,. , ;  y i-   4 : %:,,    
      `· ?    V; ` ?    
‘,—·.    
H***li￥v·?·}I§￠   ` _  ?￠is5#__·¤G$++}§;“?‘7·
  71   ’    Q  {  NH IQ
  ytéggygi {     ;g¤qg;gm·;,g(g,,3) {3;;+-
   § {Jf**$d$ }‘$p?￠L#d¤ Sc}
  ?   i `  i A1:

That's clearly gibberish that comes out of the OCR engine. So, my question is:

• What do I have to do to get better OCR results out of Tesseract?
• Or, does anybody else have better luck extracting the code from the above image in another way?

question from:https://stackoverflow.com/questions/2418722/extracting-code-from-photograph-of-t-shirt-via-ocr

Answer 1

You can probably type faster than you can clean up images and install OCR engines:

#!/usr/bin/perl
(my$d=q[AA                GTCAGTTCCT
  CGCTATGTA                 ACACACACCA
    TTTGTGAGT                ATGTAACATA
      CTCGCTGGC              TATGTCAGAC
        AGATTGATC          GATCGATAGA
          ATGATAGATC     GAACGAGTGA
            TAGATAGAGT GATAGATAGA
              GAGAGA GATAGAACGA
                TC GATAGAGAGA
                 TAGATAGACA G
               ATCGAGAGAC AGATA
             GAACGACAGA TAGATAGAT
           TGAGTGATAG    ACTGAGAGAT
         AGATAGATTG        ATAGATAGAT
       AGATAGATAG           ACTGATAGAT
     AGAGTGATAG             ATAGAATGAG
   AGATAGACAG               ACAGACAGAT
  AGATAGACAG               AGAGACAGAT
  TGATAGATAG             ATAGATAGAT
  TGATAGATAG           AATGATAGAT
   AGATTGAGTG        ACAGATCGAT
     AGAACCTTTCT   CAGTAACAGT
       CTTTCTCGC TGGCTTGCTT
         TCTAA CAACCTTACT
           G ACTGCCTTTC
           TGAGATAGAT CGA
         TAGATAGATA GACAGAC
       AGATAGATAG  ATAGAATGAC
     AGACAGAGAG      ACAGAATGAT
   CGAGAGACAG          ATAGATAGAT
  AGAATGATAG             ACAGATAGAC
  AGATAGATAG               ACAGACAGAT
  AGACAGACTG                 ATAGATAGAT
   AGATAGATAG                 AATGACAGAT
     CGATTGAATG               ACAGATAGAT
       CGACAGATAG             ATAGACAGAT
         AGAGTGATAG          ATTGATCGAC
           TGATTGATAG      ACTGATTGAT
             AGACAGATAG  AGTGACAGAT
               CGACAGA TAGATAGATA
                 GATA GATAGATAG
                    ATAGACAGA G
                  AGATAGATAG ACA
                GTCGCAAGTTC GCTCACA
])=~s/s+//g;%a=map{chr $_=>$i++}65,84,67,
71;$p=join$;,keys%a;while($d=~/([$p]{4})/g
){next if$j++%96>=16;$c=0;for$d(0..3){$c+=
$a{substr($1,$d,1)}*(4**$d)}$perl.=chr $c}
             eval $perl;

Edit: typo.