Paper Info
Title
A Robust Algorithm For Text Extraction From Images
Abstract
A robust algorithm that detects text from natural scene images and extracts them regardless of the orientation is proposed. All existing methods are designed to operate under a certain constraint, like detecting text only in one direction. Maximally Stable Extremal Regions (MSER) detector is chosen to extract binary regions since it has proven to be robust to lighting conditions. An enhancement technique for MSER images is designed to obtain clear letter boundaries. Images are then fed into a Stroke Width Detector and several heuristics are applied to remove non-text pixels. Afterwards, detected text regions are fed into an Optical Character Recognition module and then filtered according to their confidence measure. The recognition of characters is not part of the algorithm and the results are only about the detection of text. Our algorithm proved to be effective on blurred images and noisy images as well, based on both subjective and objective evaluations.
Year
Venue
Keywords
2016
2016 39TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP)
MSER, OCR, Segmentation, SWD, Text Extraction
Field
DocType
Citations 
Computer science,Robustness (computer science),Heuristics,Artificial intelligence,Detector,Computer vision,Algorithm design,Pattern recognition,Algorithm,Filter (signal processing),Optical character recognition,Maximally stable extremal regions,Pixel
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Najwa-Maria Chidiac100.34
Pascal Damien200.34
Charles Yaacoub38314.28