PT Unknown
AU Albert Gordo
   Jaume Gibert
   Ernest Valveny
   Marçal Rusiñol
TI A Kernel-based Approach to Document Retrieval
BT 9th IAPR International Workshop on Document Analysis Systems
PY 2010
BP 377–384
DI 10.1145/1815330.1815379
AB In this paper we tackle the problem of document image retrieval by combining a similarity measure between documents and the probability that a given document belongs to a certain class. The membership probability to a specific class is computed using Support Vector Machines in conjunction with similarity measure based kernel applied to structural document representations. In the presented experiments, we use different document representations, both visual and structural, and we apply them to a database of historical documents. We show how our method based on similarity kernels outperforms the usual distance-based retrieval.
ER