Using Entropy to Distinguish Shape Versus Text in Hand-Drawn Diagrams
Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence. Pages 1395-1399.
Abstract
Most sketch recognition systems are accurate in recognizing either text or shape (graphic) ink strokes, but not both. Distinguishing between shape and text strokes is, therefore, a critical task in recognizing hand drawn digital ink diagrams which commonly contain many text labels and annotations. We have found the ‘entropy rate’ to be an accurate criterion of classification. We found that the entropy rate is significantly higher for text strokes compared to shape strokes and can serve as a distinguishing factor between the two. Using entropy values, our system produced a correct classification rate of 92.06% on test data belonging to diagrammatic domain for which the threshold was trained on. It also performed favorably on data for which no training examples at all were supplied.Akshay Bhat, Tracy Anne Hammond
@inproceedings{ijcai2009p234,
title = {Using Entropy to Distinguish Shape Versus Text in Hand-Drawn Diagrams},
author = {Bhat, Akshay and Hammond, Tracy},
booktitle = {Proceedings of the Twenty-First International Joint Conference on
Artificial Intelligence, {IJCAI-09}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Hiroaki Kitano},
pages = {1395--1399},
year = {2009},
url = {https://ijcai.org/proceedings/2009/234},
}
TY - CPAPER TI - Using Entropy to Distinguish Shape Versus Text in Hand-Drawn Diagrams AU - Bhat, Akshay AU - Hammond, Tracy T2 - Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence, IJCAI-09 PB - International Joint Conferences on Artificial Intelligence PY - 2009 SP - 1395 EP - 1399 UR - https://ijcai.org/proceedings/2009/234 ER -Copied
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