A new method for image segmentation
Computer Vision, Graphics, and Image Processing
Binarising Camera Images for OCR
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Historical Document Image Enhancement Using Background Light Intensity Normalization
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Improving the Quality of Degraded Document Images
DIAL '06 Proceedings of the Second International Conference on Document Image Analysis for Libraries
Binarization of Badly Illuminated Document Images through Shading Estimation and Compensation
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
Document image binarization using background estimation and stroke edges
International Journal on Document Analysis and Recognition
Contrast enhancement using brightness preserving bi-histogram equalization
IEEE Transactions on Consumer Electronics
IEEE Transactions on Consumer Electronics
Automatic white balance for digital still camera
IEEE Transactions on Consumer Electronics
An advanced contrast enhancement using partially overlapped sub-block histogram equalization
IEEE Transactions on Circuits and Systems for Video Technology
Efficient light balancing techniques for text images in video presentation systems
IEEE Transactions on Circuits and Systems for Video Technology
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With the great advantages of digitization, more and more documents are being transformed into digital representations. Most content digitization of documents is performed by scanners or digital cameras. However, the transformation might degrade the image quality caused by lighting variations, i.e. uneven illumination distribution. In this paper we describe a new approach for text images to compensate uneven illumination distribution with a high degree of text recognition. Our proposed scheme is implemented by enhancing the contrast of the scanned documents, and then generating an edge map from the contrast-enhanced image for locating text area. With the information of the text location, a light distribution image (background) is created to assist the producing of the final light balanced image. Simulation results demonstrate that our approach is superior to the previous works of Hsia et al. (2005, 2006).