Structural Rectification of Non-planar Document Images: Application to Graphics Recognition
GREC '01 Selected Papers from the Fourth International Workshop on Graphics Recognition Algorithms and Applications
A Cylindrical Surface Model to Rectify the Bound Document Image
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Flattening Curved Documents in Images
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Perspective rectification of document images using fuzzy set and morphological operations
Image and Vision Computing
Automated Book Reader Design for Persons with Blindness
ICCHP '08 Proceedings of the 11th international conference on Computers Helping People with Special Needs
Textline information extraction from grayscale camera-captured document images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Enhancing document images acquired using portable digital cameras
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
A page content independent book dewarping method to handle 2D images captured by a digital camera
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Text extraction from natural scene image: A survey
Neurocomputing
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This paper presents a document restoration technique that is able to flatten curled document images captured through a digital camera. The proposed method corrects camera images of documents through image partition, which divides distorted text lines into multiple small patches based on the identified vertical stroke boundary (VSB) and the fitted x-line and baseline of text lines. Target rectangles are then constructed through the exploitation of the characters enclosed within the partitioned image patches. With the constructed target rectangles and the partitioned image patches, global geometric distortion is finally removed through the local rectification of partitioned image patches one by one. Experimental results show that the proposed technique is fast, accurate, and easy for implementation.