@inproceedings{scholars948,
            year = {2010},
           title = {A simple approach for text segmentation in images based on curvelet transform},
         journal = {2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010},
             doi = {10.1109/ICIAS.2010.5716245},
         address = {Kuala Lumpur},
            note = {cited By 3; Conference of 2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010 ; Conference Date: 15 June 2010 Through 17 June 2010; Conference Code:84196},
            isbn = {9781424466238},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952749216&doi=10.1109\%2fICIAS.2010.5716245&partnerID=40&md5=9dc480d3f059d71048db26a38b501e09},
          author = {Doma, M. A. M. and Faye, I. and Jeoti, V.},
        abstract = {Text segmentation in image has become an active research area since recent decades. In this paper we present an efficient simple method to extract text regions from images possibly with complex background. The proposed method is to apply curvelet transform on an image to decompose it into set of directional sub-bands with texture details captured in different orientations and scales. Curvelets possess the main features of wavelets, namely, multi scale and time-frequency localization, but also offer a high degree of directionality and anisotropy. Instead of recognizing the edges in only horizontal, vertical \& diagonal directions, the proposed system is designed to recognize the edges in multi directions taking care of text orientation. The proposed method is applied on different samples of images and encouraging results are obtained.},
        keywords = {Complex background; Curvelet transforms; Curvelets; Multiscales; Research areas; Simple approach; SIMPLE method; Sub-bands; Text region; Text segmentation; Time-frequency localization, Character recognition, Image segmentation}
}