A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Fields of Experts: A Framework for Learning Image Priors
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Skew detection using wavelet decomposition and projection profile analysis
Pattern Recognition Letters
Text segmentation in color images using tensor voting
Image and Vision Computing
Color text extraction with selective metric-based clustering
Computer Vision and Image Understanding
Non-negative sparse coding shrinkage for image denoising using normal inverse Gaussian density model
Image and Vision Computing
Normal mesh based geometrical image compression
Image and Vision Computing
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Figure-ground segmentation using factor graphs
Image and Vision Computing
Accurate text localization in images based on SVM output scores
Image and Vision Computing
IBM Journal of Research and Development
Fast and robust text detection in images and video frames
Image and Vision Computing
A two-stage scheme for text detection in video images
Image and Vision Computing
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Robust detection of skew in document images
IEEE Transactions on Image Processing
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
Text Extraction and Document Image Segmentation Using Matched Wavelets and MRF Model
IEEE Transactions on Image Processing
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
A comprehensive method for multilingual video text detection, localization, and extraction
IEEE Transactions on Circuits and Systems for Video Technology
Using adaptive run length smoothing algorithm for accurate text localization in images
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Sulci detection in photos of the human cortex based on learned discriminative dictionaries
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
T-HOG: An effective gradient-based descriptor for single line text regions
Pattern Recognition
Text extraction from scene images by character appearance and structure modeling
Computer Vision and Image Understanding
A framework for improved video text detection and recognition
Multimedia Tools and Applications
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Text detection is important in the retrieval of texts from digital pictures, video databases and webpages. However, it can be very challenging since the text is often embedded in a complex background. In this paper, we propose a classification-based algorithm for text detection using a sparse representation with discriminative dictionaries. First, the edges are detected by the wavelet transform and scanned into patches by a sliding window. Then, candidate text areas are obtained by applying a simple classification procedure using two learned discriminative dictionaries. Finally, the adaptive run-length smoothing algorithm and projection profile analysis are used to further refine the candidate text areas. The proposed method is evaluated on the Microsoft common test set, the ICDAR 2003 text locating set, and an image set collected from the web. Extensive experiments show that the proposed method can effectively detect texts of various sizes, fonts and colors from images and videos.