"Adaptive document image thresholding using foreground and background clustering," Proceedings of the 1998 International Conference on Image Processing (ICIP '98). The Institute of Electrical and Electronics Engineers. Held in Chicago, Illinois: 4-7 October 1998. ©1998 Institute of Electrical and Electronics Engineers (IEEE). Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. Two algorithms for document image thresholding are presented, that are suitable for scanning document images at high-speed. They are designed to operate on a portion of the image while scanning the document, thus, they fit a pipeline architecture and lend themselves to real-time implementation. The first algorithm is based on adaptive thresholding and uses local edge information to switch between global thresholding and adaptive local thresholding determined from the statistics of a local image window. The second thresholding algorithm is based on tracking the foreground and background levels using clustering based on a variant of the K-means algorithm. The two approaches may be used independently or may be combined for improved pe$ormance. Results are presented illustrating the algorithms' performance for document and pictorial images.
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Chester F. Carlson Center for Imaging Science (COS)
Savakis, Andreas, "Adaptive document image thresholding using foreground and background clustering" (1998). Image Processing. The Institute of Electrical and Electronics Engineers (IEEE), vol. 3 (), 785-789. Accessed from
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