2015/04/14 by Lukáš Neumann, Jiří Matas, Neumann, Lukáš +2
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Mathematics, Computing, and Information Processing #Natural Language Processing Techniques #Vehicle License Plate Recognition #cs.CV
paper · pdf · doi:10.48550/arxiv.1504.03522
arxiv created 2015/04/14 · openalex publication_date 2015/04/14 · arxiv updated 2015/04/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
An unconstrained end-to-end text localization and recognition method is presented. The method detects initial text hypothesis in a single pass by an efficient region-based method and subsequently refines the text hypothesis using a more robust local text model, which deviates from the common assumption of region-based methods that all characters are detected as connected components. Additionally, a novel feature based on character stroke area estimation is introduced. The feature is efficiently computed from a region distance map, it is invariant to scaling and rotations and allows to efficiently detect text regions regardless of what portion of text they capture. The method runs in real time and achieves state-of-the-art text localization and recognition results on the ICDAR 2013 Robust Reading dataset.