TY  - JOUR
AU  - Sounak Dey
AU  - Anguelos Nicolaou
AU  - Josep Llados
AU  - Umapada Pal
PY  - 2019//
TI  - Evaluation of the Effect of Improper Segmentation on Word Spotting
T2  - IJDAR
JO  - International Journal on Document Analysis and Recognition
SP  - 361
EP  - 374
VL  - 22
N2  - 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.
UR  - https://link.springer.com/article/10.1007/s10032-019-00338-9
L1  - http://refbase.cvc.uab.es/files/DNL2019.pdf
N1  - DAG; 600.097; 600.084; 600.121; 600.140; 600.129
ID  - Sounak Dey2019
ER  -