## ICFHR 2014 CROHME: Fourth International Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME-2014)

## Research Tasks

# Mathematical Expression Recognition

2015-02-16 (v. 1)

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### Description

The difficulty to recognize mathematical expressions depends of the number of different symbols, number of allowed layouts and the used grammar. The competition define 4 levels (tasks) from 41 symbols to 101 symbols, with increasing difficulties in the grammar of allowed expressions.

### Protocol

The competition defines an evaluation protocol :

- participants can use available training dataset (and more)
- the candidate systems take as input an inkml file (without ground-truth) and have to write as output a inkml file with the symbol segmentation, recognition and the expression interpretation with MathML format. This is exactly the same format as the provided training dataset. Since 2013, the system can also generate label graph (LG) files.
- the evaluation first converts the inkml files in LG files and then compare the resulting inkml and LG files with the ground-truth with a provided script.

Several aspects are measured. They are

- ST_Rec: the stroke classification rate, representing the percentage of strokes with the correct symbol,
- SYM_Seg: the symbol segmentation rate, defining the percentage of symbols correctly segmented,
- SYM_Rec; the symbol recognition rate, computing the performance of the symbol classifier when considering only the correct segmented symbols,
- STRUCT: the MathML structure recognition rate, computing the percentage of expressions (MEs) having the correct MathML tree as output irrespective of the symbols attached to its leaves.
- EXP_Rec: the expression recognition rate, which informs the percentage of MEs totally correctly recognized.
- EXP-Rec_1, _2, _3, giving the percentage of MEs recognized with at most 1 error, 2 errors and 3 errors (in terminal symbols or in MathML node tags) given that the tree structure is correct.
- Recall and Precision for segments and recognized segments (symbols)
- Recall and Precision for spatial relations between the symbols

As the MathML struture is not unique for the same expressions, the evaluation tool provides a normalization step to use canonical structures.

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