Text segmentation using Gabor filters for automatic document processing
Machine Vision and Applications - Special issue: document image analysis techniques
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Automatic location of text in video frames
MULTIMEDIA '01 Proceedings of the 2001 ACM workshops on Multimedia: multimedia information retrieval
Text Detection in Images Based on Unsupervised Classification of Edge-based Features
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Text segmentation based on stroke filter
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
An efficient method for text detection in video based on stroke width similarity
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
A spatial-temporal approach for video caption detection and recognition
IEEE Transactions on Neural Networks
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Captions in videos provide much useful semantic information for indexing and retrieving video contents. In this paper, we present an effective approach to extracting captions from videos. Its novelty comes from exploiting the temporal information in both localization and segmentation of captions. Since some simple features such as edges, corners and color are utilized, our approach is efficient. It involves four steps. First, we exploit the distribution of corners to spatially detect and locate the caption in a frame. Then the temporal localization for different captions in a video is performed by identifying the change of stroke directions. After that, we segment the caption pixels in a clip with a same caption based on the consistency and dominant distribution of caption color. Finally, the segmentation results are further refined. The experimental results on two representative movies have preliminarily verified the validity of our approach.