A novel ring radius transform for video character reconstruction
Pattern Recognition
Scene text detection using graph model built upon maximally stable extremal regions
Pattern Recognition Letters
Graph-Based detection of objects with regular regions
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part III
A phase-based approach for caption detection in videos
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Scale based region growing for scene text detection
Proceedings of the 21st ACM international conference on Multimedia
Hi-index | 0.14 |
Abstract—In this paper, we propose a method based on the Laplacian in the frequency domain for video text detection. Unlike many other approaches which assume that text is horizontally-oriented, our method is able to handle text of arbitrary orientation. The input image is first filtered with Fourier-Laplacian. K--means clustering is then used to identify candidate text regions based on the maximum difference. The skeleton of each connected component helps to separate the different text strings from each other. Finally, text string straightness and edge density are used for false positive elimination. Experimental results show that the proposed method is able to handle graphics text and scene text of both horizontal and nonhorizontal orientation.