PT Journal
AU Sounak Dey
   Anguelos Nicolaou
   Josep Llados
   Umapada Pal
TI Evaluation of the Effect of Improper Segmentation on Word Spotting
SO International Journal on Document Analysis and Recognition
JI IJDAR
PY 2019
BP 361
EP 374
VL 22
AB Word spotting is an important recognition task in large-scale retrieval of document collections. In most of the cases, methods are developed and evaluated assuming perfect word segmentation. In this paper, we propose an experimental framework to quantify the goodness that word segmentation has on the performance achieved by word spotting methods in identical unbiased conditions. The framework consists of generating systematic distortions on segmentation and retrieving the original queries from the distorted dataset. We have tested our framework on several established and state-of-the-art methods using George Washington and Barcelona Marriage Datasets. The experiments done allow for an estimate of the end-to-end performance of word spotting methods.
ER