Text Classification on ICDAR

We evaluated our text detection algorithm on ICDAR benchmark. More information can be found here: http://dag.cvc.uab.es/icdar2013competition

We run our algorithm on Challenge 1, Task 2.  Our text detection results can be found in this webpage:
https://dl.dropboxusercontent.com/u/20022261/reports/text_segmentation_benchmark_ICAR.html

The baseline excludes the characters that are merged as missed results. However, we have no interest in making that computation. We compute precision and recall given:

Precision=tp/(tp+fp)

Recall= tp/(tp+mr)

where tp is true positive count, fp is false positive and mr is missed rate. In that case the accuracy of the other algorithms would be as follows:

  precision   recall   f-measure

    0.9252    0.9515    0.9384

    0.8566    0.9094    0.8830

    0.8544    0.8689    0.8617

    0.7708    0.9737    0.8722

    0.8248    0.9638    0.8943

Ours

    0.9083    0.8837    0.8960