Detecting texts of arbitrary orientations in natural images

With the increasing popularity of practical vision systems and smart phones, text detection in natural scenes becomes a critical yet challenging task. Most existing methods have focused on detecting horizontal or near-horizontal texts. In this paper, we propose a system which detects texts of arbitr...

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Bibliographic Details
Published in:2012 IEEE Conference on Computer Vision and Pattern Recognition pp. 1083 - 1090
Main Authors: Cong Yao, Xiang Bai, Wenyu Liu, Yi Ma, Zhuowen Tu
Format: Conference Proceeding
Language:English
Published: IEEE 01.06.2012
Subjects:
Algorithm design and analysis
Clutter
Histograms
Image edge detection
Joining processes
Robustness
Shape
ISBN:9781467312264, 1467312266
ISSN:1063-6919, 1063-6919
Online Access:Get full text
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Summary:With the increasing popularity of practical vision systems and smart phones, text detection in natural scenes becomes a critical yet challenging task. Most existing methods have focused on detecting horizontal or near-horizontal texts. In this paper, we propose a system which detects texts of arbitrary orientations in natural images. Our algorithm is equipped with a two-level classification scheme and two sets of features specially designed for capturing both the intrinsic characteristics of texts. To better evaluate our algorithm and compare it with other competing algorithms, we generate a new dataset, which includes various texts in diverse real-world scenarios; we also propose a protocol for performance evaluation. Experiments on benchmark datasets and the proposed dataset demonstrate that our algorithm compares favorably with the state-of-the-art algorithms when handling horizontal texts and achieves significantly enhanced performance on texts of arbitrary orientations in complex natural scenes.
ISBN:9781467312264
1467312266
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2012.6247787