Title :
Sketch-Based Retrieval of Document Illustrations and Regions of Interest
Author :
Tencer, Lukas ; Renakova, Marta ; Cheriet, Mohamed
Author_Institution :
Dept. de Genie de la Production Automatisee, Ecole de Technol. Super., Montreal, QC, Canada
Abstract :
In this paper we present a novel approach towards retrieval of documents with pictorial data. Many prior works focused on word-spotting and text-based retrieval, but none of these techniques handled the retrieval of pictorial part of documents. In this paper, we present a new method that allows users to retrieve any visual data from documents, based on a sketch example. It mainly emphasizes all three main aspects of a visual retrieval system: feature representation, indexing and retrieval. Especially we focus on the design of salient descriptors, capable of capturing unique mapping from sketched images to document illustrations. We evaluate several approaches towards feature representation and indexing, with the aim to maximize the performance of our method. Our proposed technique is highly useful to complement word-spotting technique, when the indexed documents are composed of mixture of visual and textual data. This technique has shown promising results, both on pictorial data automatically extracted from documents as well for those selected by users as regions of interest.
Keywords :
document image processing; image retrieval; text detection; document illustrations; feature representation; indexing; pictorial data; regions of interest; sketch-based retrieval; sketched images; text-based retrieval; visual retrieval system; word-spotting technique; Feature extraction; Hidden Markov models; Histograms; Image edge detection; Indexing; Visualization; BoW; DDT; EHD; HOG; Inverted Index; SIFT; feature evaluation; indexing; sketch-based retrieval; visual retrieval;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location :
Washington, DC
DOI :
10.1109/ICDAR.2013.149