Text Detection in Natural Scene Images by Stroke Gabor Words
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
Text String Detection From Natural Scenes by Structure-Based Partition and Grouping
IEEE Transactions on Image Processing
A Novel Text Detection Approach Based on Multi-Structure Element of Morphology
ICICEE '12 Proceedings of the 2012 International Conference on Industrial Control and Electronics Engineering
Scene text detection using graph model built upon maximally stable extremal regions
Pattern Recognition Letters
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A text location algorithm in color images which is suitable to run on entry-level smartphones is proposed to overcome the weaker computing power on smartphones than on computers. In our proposed algorithm, first, morphological approaches are used to do with the edge image and so single text character or text string will form a connected component (CC), namely, the candidate text region. Then, non-text regions are excluded from the candidate text regions by using improved heuristic constraints based on the Gaussian image pyramid and mergence of adjacent connected components which is firstly proposed in this paper. Experiment demonstrates that in terms of the speed, this algorithm runs fast on an entry-level smartphone by only using edge information and in terms of the performance, this algorithm can be used to locate horizontal text lines in different font size, language, and color and it's easy to adapt it to locate vertical text lines. The algorithm effectively solves the problem of high false alarm probability in edge-based methods and gets high precision and recall rate.