A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Scene Text Segmentation with Multi-level Maximally Stable Extremal Regions
2014
2014 22nd International Conference on Pattern Recognition
The segmentation of scene text from the image background has shown great importance in scene text recognition. In this paper, we propose a multi-level MSER technology that identifies the best-quality text candidates from a set of stable regions that are extracted from different color channel images. In order to identify the best-quality text candidates, a segmentation score is defined which exploits four measures to evaluate the text probability of each stable region including: 1) Stroke width
doi:10.1109/icpr.2014.467
dblp:conf/icpr/TianLST14
fatcat:nzi7x24smjdrfk552whhlwenry