This weekly report summarizes work from a multidisciplinary workshop. It describes extracting features from 40x40 pixel images using histograms and setting the image region. Character recognition was performed using an artificial neural network to recognize 44 characters with an accuracy of 44%. The report was submitted by Mrs. Marin Rattanapapra, student ID 53211823, to the Department of Control System and Instrumentation Engineering at King Mongkut's University of Technology Thonburi.

1. [INC 281 Multidisciplinary workshop weekly report]
April 4, 2012
Mrs. Marin Rattanapapra (You)
Name-Surname
.
Student ID. 53211823
4
“ ”
- (Set Region)
Histogram
40x40
(Feature Extraction)
-
(Character recognition)
Artificial Neural Network
44
Department of Control System and Instrumentation Engineering
KING MONGKUT’s UNIVERSITY OF TECHNOLOGY THONBURI

2. [INC 281 Multidisciplinary workshop weekly report]
April 4, 2012
Department of Control System and Instrumentation Engineering
KING MONGKUT’s UNIVERSITY OF TECHNOLOGY THONBURI