This paper explores a combination of machine learning, approximate text segmentation and a vector-space model to distinguish novel information from repeated information. In experiments with the data from the Novelty Track at the Text Retrieval Conference, we show improvements over a variety of approaches, in particular in raising precision scores on this data, while maintaining a reasonable amo...

Arbitrary-shaped text detection has recently attracted increasing interests and witnessed rapid development with the popularity of deep learning algorithms. Nevertheless, existing approaches often obtain inaccurate results, mainly due to relatively weak ability utilize context information inappropriate choice offset references. This paper presents a novel instance expression which integrates bo...

This paper proposes a new hierarchical MDL-based model for a joint detection and classification of multilingual text lines in images taken by hand-held cameras. The majority of related text detection methods assume alphabet-based writing in a single language, e.g. in Latin. They use simple clustering heuristics specific to such texts: proximity between letters within one line, larger distance b...