Techniques and Systems for Image and Video Retrieval
IEEE Transactions on Knowledge and Data Engineering
Binarising Camera Images for OCR
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Extraction and recognition of artificial text in multimedia documents
Pattern Analysis & Applications
Text Detection in Images Based on Unsupervised Classification of High-Frequency Wavelet Coefficients
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
A Novel Video Caption Detection Approach Using Multi-Frame Integration
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Scene Text Extraction in Natural Scene Images using Hierarchical Feature Combining and Verification
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
A discriminative feature space for detecting and recognizing faces
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Morphological text extraction from images
IEEE Transactions on Image Processing
Localizing and segmenting text in images and videos
IEEE Transactions on Circuits and Systems for Video Technology
Automatic text discovering through stroke-based segmentation and text string combination
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Text extraction using component analysis and neuro-fuzzy classification on complex backgrounds
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
| Hi-index | 0.00 |
In this paper we present a novel video text detection and segmentation system. In the detection stage, we utilize edge density feature, pyramid strategy and some weak rules to search for text regions, so that high detection rate can be achieved. Meanwhile, to eliminate the false alarms and improve the precision rate, a multilevel verification strategy is adopted. In the segmentation stage, a precise polarity estimation algorithm is firstly provided. Then, multiple frames containing the same text are integrated to enhance the contrast between text and background. Finally, a novel connected components based binarization algorithm is proposed to improve the recognition rate. Experimental results show the superior performance of the proposed system.