A comprehensive method for multilingual video text detection, localization, and extraction

By Michael R. Lyu, Jiqiang Song, Min Cai. IEEE transactions on circuits and systems for video technology (Print), 2005

379 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Text Detection and Recognition in Imagery: A Survey (2015, methodology): “The pattern differences in detection arise from the font sizes and stroke distributions and are not as critical as the pattern diversity in recognition [45], which is related to character structures, shapes and class number.”
Scene text detection and recognition: recent advances and future trends (2015, neutral): “[40] proposed a coarse-to-fine multiscale search scheme.”
A Unified Framework for Multioriented Text Detection and Recognition (2014, methodology): “Driven by the wide range of potential applications, scene text detection and recognition have been important research topics for decades [7], [8], [35]–[41] and have recently seen a surge in research efforts in the computer vision community [9]–[14], [17], [18], [20], [21], [26], [42].”
Comparative study on methods of detecting research fronts using different types of citation (2009, methodology): “We then employed the edge-based filtering method ( Lyu, Song, & Cai, 2005; Sasaki, Lin, Chen, & Chen, 2007) to eliminate the nontext pixels.”
A Hybrid Approach to Detect and Localize Texts in Natural Scene Images (2011, result): “Similarly with the image pyramid, Lyu et al. [24] detect candidate text edges of various scales with a Sobel operator.”