scttl/marks_based_ocr

Matlab based document image analysis and classification system, that makes heavy use of contextual and language cues to decode image glyphs

Marks Based OCR
===============
Relatively complete document image analysis system that largely ignores image 
information during the classification stage.  Instead relies on contextual and 
language cues.

Developed by Scott Leishman for research purposes while attending U of T.


1. INSTALLING
-------------

1.1 - Requirements
------------------

* Matlab 7 or higher  (earlier versions won't work due to use of imview and
                       find(...'first') etc.)

1.2 - Notes
-----------

* Copy all files (and subdirs) in this directory to some location on the users
  computer (note this location -- we'll denote it INS_PATH).

* Add the following lines to your ~/matlab/startup.m (or type it from the
  Matlab command prompt):

  global MOCR_PATH;
  MOCR_PATH = 'INS_PATH';
  addpath(MOCR_PATH);
  marks_ocr_init;


(where INS_PATH is replaced by the actual path to where the files and subdirs
 were installed)


2. Configuration
----------------

Typically, modifiable parameters are found at the top of key files before
being passed on to other functions as neccessary.  Descriptions of each 
parameter are located within such a file and sensible defaults are already
defined.

* for clustering and connected components, see cluster/cluster_comps.m

* for line finding, see util/get_lines.m

* ...


3. Running
----------
* There are 3 main tasks: creating training data, clustering components of 
  file images and constructing a language model from them, and performing ocr
  on lines of training data, given a constructed language model.

* To create new training cases, the following commands are useful:

* ...