Unsupervised word spotting using a graph representation based on invariants

Abstract

We are currently working on the concept of an interactive word retrieval system for ancient document collection navigation, based on query composition for non-expert users. We have introduced a new notion: invariants, which are writing pieces automatically extracted from the old document collection. The invariants can be used in query making process in where the user selects and composes appropriate invariants to make the query. The invariants can be also used as descriptor to characterize word images. We introduced our unsupervised method for extracting invariants in our earlier paper. In this paper, we present a new structural word spotting system using a graph representation based on invariants as a descriptor. Through experiments, we conclude that our proposed system can adapt to different types of homogenous alphabetic languages documents (regardless of language/script, antiquity, handwritten or printed).