Cuneiform Symbols Recognition Using Intensity Curves

Recognition of Handwritten Persian Numbers and Arithmetic Symbols Using Neural Networks

Recognition of Handwritten Persian Numbers and Arithmetic Symbols Using Neural Networks

Symbol Spotting using Full Visibility Graph Representation

In this paper, a method for matching symbols in line-drawings is presented. Facing both segmentation and recognition of symbols is a difficult challenge. Starting from the results of a vectorization procedure, a visibility graph is built to enhance the main geometric constraints which were specified during the construction of the initial document. The cliques detection, which correspond to a pe...

Enhancing Sumerian Lemmatization by Unsupervised Named-Entity Recognition

Lemmatization for the Sumerian language, compared to the modern languages, is much more challenging due to that it is a long dead language, highly skilled language experts are extremely scarce and more and more Sumerian texts are coming out. This paper describes how our unsupervised Sumerian named-entity recognition (NER) system helps to improve the lemmatization of the Cuneiform Digital Librar...

Detection of a polymorphic Mesoamerican symbol using a rule-based approach

This paper describes a technique to recognize a Mesoamerican symbol whose shape is extremely variable. We extract symbols from a drawing and we encode them as discrete curves. We perform the recognition using a set of rules that define the correct symbol. One of the rules is the presence of a single symmetry axis. We describe a comparison metric between curves in order to search for symmetries....