A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Caption Localization in Compressed Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Video OCR for Digital News Archive
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Identification of Text on Colored Book and Journal Covers
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Automatic text recognition in digital videos
Automatic text recognition in digital videos
Fast and robust text detection in images and video frames
Image and Vision Computing
Performance evaluation of text detection and tracking in video
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Localizing and segmenting text in images and videos
IEEE Transactions on Circuits and Systems for Video Technology
An automatic performance evaluation protocol for video text detection algorithms
IEEE Transactions on Circuits and Systems for Video Technology
Toward a conceptual framework of key-frame extraction and storyboard display for video summarization
Journal of the American Society for Information Science and Technology
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In this paper we propose an edge-based algorithm for artificial text detection in video frames. First, an edge map is created using the Canny edge detector. Then, morphological filtering is used, based on geometrical constraints, in order to connect the vertical edges and discard false alarms. A connected component analysis is performed to the filtered edge map in order to determine a bounding box for every candidate text area. Finally, horizontal and vertical projections are calculated on the edge map of every box and a threshold is applied, refining the result and splitting text areas in text lines. The whole algorithm is applied in multiresolution fashion to ensure text detection with size variability. Experimental results prove that the method is highly effective and efficient for artificial text detection.