TY  - CONF
AU  - Anders Hast
AU  - Alicia Fornes
A2  - DAS
PY  - 2016//
TI  - A Segmentation-free Handwritten Word Spotting Approach by Relaxed Feature Matching
BT  - 12th IAPR Workshop on Document Analysis Systems
SP  - 150
EP  - 155
N2  - The automatic recognition of historical handwritten documents is still considered  challenging task. For this reason, word spotting emerges as a good alternative for making the information contained in these documents available to the user. Word spotting is defined as the task of retrieving all instances of the query word in a document collection, becoming a useful tool for information retrieval. In this paper we propose a segmentation-free word spotting approach able to deal with large document collections. Our method is inspired on feature matching algorithms that have been applied to image matching and retrieval. Since handwritten words have different shape, there is no exact transformation to be obtained. However, the sufficient degree of relaxation is achieved by using a Fourier based descriptor and an alternative approach to RANSAC called PUMA. The proposed approach is evaluated on historical marriage records, achieving promising results.
L1  - http://refbase.cvc.uab.es/files/HaF2016.pdf
UR  - http://dx.doi.org/10.1109/DAS.2016.40
N1  - DAG; 602.006; 600.061; 600.077; 600.097
ID  - Anders Hast2016
ER  -