Problem Tool Harder problem Experiments Result Optical Character Recognition using Bayesian Networks Ioannis Klasinas iklasinas@telecom.tuc.gr July 11, 2007 Ioannis Klasinas iklasinas@telecom.tuc.gr Optical Character Recognition using Bayesian Networks
Problem Tool Harder problem Experiments Result Problem Letter Recognition Using Holland-Style Adptive Classifiers , Peter W. Frey, David J. Slate English capital letters 20000 instances (bitmap fonts) 45x45 pixel bitmap Images distorted (linear magnification, aspect radio, horizontal/vertical wrap) 16 features extracted 82.7% accuracy Others 93,6% (Statlog ALLOC80) Ioannis Klasinas iklasinas@telecom.tuc.gr Optical Character Recognition using Bayesian Networks
Problem Tool Harder problem Experiments Result Weka Weka (http://www.cs.waikato.ac.nz/ml/weka/) Various classification methods Used Bayes networks 87.5% accuracy, 4 parents per node Ioannis Klasinas iklasinas@telecom.tuc.gr Optical Character Recognition using Bayesian Networks
Problem Tool Harder problem Experiments Result Digit OCR Scanned handwritten digits 16x16 grayscale bitmaps 9200 instances Threshold to convert to b/w Extracted features Normalized as above NRR-1:94.5%, Bayes:38.2% Ioannis Klasinas iklasinas@telecom.tuc.gr Optical Character Recognition using Bayesian Networks
Problem Tool Harder problem Experiments Result Experiments Experimented with 1 threshold 2 max parents number Best result for threshold=0.2, max parents=16 Ioannis Klasinas iklasinas@telecom.tuc.gr Optical Character Recognition using Bayesian Networks
Problem Tool Harder problem Experiments Result Threshold Figure: Bitmaps, for threshold -0.5/0/0.5 Ioannis Klasinas iklasinas@telecom.tuc.gr Optical Character Recognition using Bayesian Networks
84 th=-0.5 th=-0.4 th=-0.3 83 th=-0.2 th=-0.1 th=0 82 th=0.1 th=0.2 th=0.3 81 th=0.4 80 79 78 77 76 75 74 0 2 4 6 8 10 12 14 16 18 Figure: Results
Problem Tool Harder problem Experiments Result Discussion Handwritten OCR tough problem Weka unpredictable Bayesian networks inferior to other approaches for this problem More appropriate features needed Ioannis Klasinas iklasinas@telecom.tuc.gr Optical Character Recognition using Bayesian Networks
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