1. Paper Bibliography
- Title: Using Entropy to Distinguish Shape Versus Text in Hand-Drawn Diagrams
- Authors: Bhat, Akshay, and Tracy Hammond.
- Publication: IJCAI. Vol. 9. 2009.
2. Summary
- Distinguish between shapes and texts
- Text has higher entropy rate than shapes
- Entropy rate = distinguishing factor
- Using only the entropy rate, a correct classification rate is 92.06%
- Favorable performance without training data
3. Terminology
- Entropy rate: accurate criterion of classification
4. Details
- Entropy
- Each point in a stroke is assigned a symbol based on the angle (corresponding angle in the Table 1)
In this figure, text has various symbol compared to rectangle.
- This symbol is the random variable on the basis of which we can calculate entropy.
- Use a zero-order entropy
- each symbol's probability of occurrence is determined independent of the previous symbols.
- Define an entropy model 'alphabet'
- Implementation
- Stroke Grouping
- A spatial and temporal threshold
- The successful rate: 99.78%
- After groping
- Resample
- Transform each stroke into a string of symbols
- Calculate the percentage of the occurrence of symbols
- Classification
- Confidence Measure
- in order to integrate a classifier into other sketch recognition
- Data collecting and Testing
5. Evaluation
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