FEATURE BASED INDEXING OF 
HAND-WRITTEN TEXT IMAGES 
 
 
 
 
NAGARAJAH  KUNTHARSHAN 
 
 
This dissertation was submitted to the Department of  Computer Science and Engineering of the 
University of Moratuwa in partial fulfillment of the requirement for the Degree of M Sc in Computer 
Science 
 
 
 
Department of Computer Science and Engineering 
University ofMoratuwa 
Sri Lanka 
March 2010 
 
 
 
 
96425 
 Abstract 
Identity management system which is maintaining a manual database system to store its data is 
facing a big challenge of searching a particular entry from the database if a query rose where the date 
of birth of the person is not known. Person Identification department, as an example, the existing 
database is in the form of Pre-designed hand written physical cards with the details. The cards are 
served separated by sex and ordered by date of birth. 
 
In case of a person whose date of birth is not known, there is a challenge of going through the cards 
one by one to spot the exact record. So, person registration department decided to computerize the 
database and found out the following. Since the hand writing is very poor there is no chance of using 
character recognition software. The better option could be manually enter the data into a database, 
but quotations submitted for the tender called for this task was much higher than the 
potential level of the department. 
 
Finally, feature extraction method is found out as an ideal solution for this task. ln this approach all 
the cards are scanned and saved in the system using batch scanning. Each file is pre-processed and 
the number of characters in the name is saved to the database as index for the corresponding 
scanned image. The search operation on the database based on the number of characters of the name 
will list down the name of the possible card and the corresponding card also will be fetched from the 
saved location and previewed. Among the cards that arc identified, user needs to find the cards 
manually. 
 
This will narrow down the search. System will fail in counting the number of characters in the name 
if there is no space left between two characters or if one character is split "into two by mistake. To 
handle these challenges, a new intelligent algorithm should be generated with the ability to 
understand the order or the pattern of occurrences of the characters and make the decision based on 
them 
Declaration 
I, Nagarajah Kunatharshan hereby declare that the work included in this dissertation in 
part or whole has not been submitted for any other academic qualification at any 
institution. 
N-J~ 
Mr. N. Kunatharshan 
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DR. Chathura De Silva 
(Supervisor) 
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2 
Acknowledgements 
Having completed the MSc. Degree program at the Department of Computer Science 
and Engineering, University of Moratuwa, I would like to take this opportunity to 
thank those who helped me a lot in completing it at this level. 
First of all. I would like to thank my supervisor, Dr. Chathura De Silva for the 
supervision and guidance despite his busy schedules. Also I would like to thank Ms. 
Visaka Nanayakkara, Dr. Gihan Dias and Dr. Sanath Jayasena for conducting the subject 
Research Seminar, which helped me a lot when browsing through the published 
research papers. 
1 should be grateful to all the members of the staff of the Department of Computer 
Science and Engineering for giving valuable feed back during the progress review 
sessions. 
Finally, I would like to thank my family for supporting me in every aspect m 
completing my degree program and the research successfully. 
Thank you all! 
Kunatharshan N ... 
(06/8279) 
-.,.. 
4 
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Table of Contents 
Declaration ... ... ....................................................... .......... ... .. .. .... .. ................................. 2 
Abstract .......................................................................................................................... 3 
Acknowledgements ........................................................................................................ 4 
'fable of Contents ........................................................................................................... 5 
List of Figures ................................................................................................................ 7 
1. Introduction ..... ........................................................................................................... 8 
2. Literature Review .................................................................................................... 11 
2.1 Edges Detection: ................................................................................................ 11 
2.2 Lines Detection - Hough Transform: ................................................................ 12 
2.3 Image Registration with Template matching ............. .. .. .. ... .. ... ... ... .................... 13 
2.4 Cross-correlation ................................................................................................ 14 
2.5 Open and Close .................................................................................................. 14 
2.6 Erosion ............................................................................................................... 15 
2.7 Dilation ..................................................... :-, ....................................................... 15 
2.8 Opening .............................................................................................................. 16 
2.9 Closing .......................................... : .................................................................... 16 
2.1 0 Color Scale Conversion - gray scale" ............................................................... 17 
3. Materials and Methods ....................................................... .... . ::~ ............................ 18 
3 .1 Adding images to the system ................................. ... ......................................... 19 
3.1.1 Templateimage: ............................................... : ............ ... ........................... 19 
3.1.2 Printed Character Removal: ........................................................................ 20 
3.1.3 Removal of lines: ...................................................... .. .. ............................... 2 1 
3.1.4 Closing: ....................................................................................................... 23 
3 .1.5 Character counting: ..................................................................................... 24 
3.2 Finding images ................................................................................................... 24 
4. Observations ............................................................................................................ 25 
5 
5. Analysis and Discussion of Results ......................................................................... 26 
5.1 Binary image conversion: .................................................................................. 26 
5.2 Closing: .............................................................................................................. 27 
5.3 Line removal: ..................................................................................................... 28 
6. Conclusions and Recommendations for Future Research ....................................... 29 
7. References ................................................................................................................ 30 
8. Annexure .................................................................................................................. 32 
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List of Figures 
Figure 3.1 : Flowchart of the model .................................. ... .... .. ... .. ............................. 18 
Figure 3.2: Scanned image (Eyes and ID Numbers are masked in order to keep the 
confidentiality) ..................................................................................................... 19 
Figure 3.3: Template image ......................................................................................... 20 
Figure 3.4: Cropped Image .......................................................................................... 21 
Figure 3.5: Name surroundings after the removal of printed characters ..................... 21 
Figure 3.6: Generated line image ................................................................................. 22 
Figure 3.7: Scanned image after the line removal ....................................................... 23 
Figure 3.8: Name surroundings after the removal of lines .......................................... 23 
Figure 3.9: After the closing operation ........................................................................ 23 
Figure 3 .1 0: After the noise removal.. ......................................................................... 24 
Figure 4.1: Processed segment of hand written characters .......................................... 25 
Figure 4.2: Processed segment of printed characters ................................................... 25 
Figure 5.1: Result with binary image .......................................................................... 26 
.... 
Figure 5.2: Result with gray image .............................................................................. 27 
Figure 5.3 close with 'disk' (radius 2) morphological structuring element ................ 27 
Figure 5.4: close with 'line' (length 10, angle 90 degrees) morphological structuring 
element ................................................................................................................. 27 
...,... 
Figure 5.5: close with 'line' (length 3, angle 90 degrees) morphological structuring 
element .. .............................................................................. ... ... ........................... 28 
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