JUCS - Journal of Universal Computer Science 17(1): 64-80, doi: 10.3217/jucs-017-01-0064
The Use of Latent Semantic Indexing to Mitigate OCR Effects of Related Document Images
expand article infoRenato F. Bulcão-Neto, José A. Camacho-Guerrero, Marcio Branquinho Dutra§, Álvaro Barreiro|, Javier Parapar, Alessandra Alaniz Macedo§
‡ Innolution Sistemas de Informática Ltda., Ribeirão Preto, Brazil§ Universidade de São Paulo, Ribeirão Preto, Brazil| University of A Coruña, A Coruña, Spain¶ University of A Coruña, Coruña, Spain
Open Access
Due to both the widespread and multipurpose use of document images and the current availability of a high number of document images repositories, robust information retrieval mechanisms and systems have been increasingly demanded. This paper presents an approach to support the automatic generation of relationships among document images by exploiting Latent Semantic Indexing (LSI) and Optical Character Recognition (OCR). We developed the LinkDI (Linking of Document Images) service, which extracts and indexes document images content, computes its latent semantics, and defines relationships among images as hyperlinks. LinkDI was experimented with document images repositories, and its performance was evaluated by comparing the quality of the relationships created among textual documents as well as among their respective document images. Considering those same document images, we ran further experiments in order to compare the performance of LinkDI when it exploits or not the LSI technique. Experimental results showed that LSI can mitigate the effects of usual OCR misrecognition, which reinforces the feasibility of LinkDI relating OCR output with high degradation.
applied computing, information retrieval, document engineering, latent semantic, optical character recognition, document image, experimentation