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|Title:||Binarization of historical document images using the local maximum and minimum|
|Keywords:||Document image analysis|
Document image binarization
Image pixel classification
|Source:||Su, B.,Lu, S.,Tan, C.L. (2010). Binarization of historical document images using the local maximum and minimum. ACM International Conference Proceeding Series : 159-165. ScholarBank@NUS Repository. https://doi.org/10.1145/1815330.1815351|
|Abstract:||This paper presents a new document image binarization technique that segments the text from badly degraded historical document images. The proposed technique makes use of the image contrast that is defined by the local image maximum and minimum. Compared with the image gradient, the image contrast evaluated by the local maximum and minimum has a nice property that it is more tolerant to the uneven illumination and other types of document degradation such as smear. Given a historical document image, the proposed technique first constructs a contrast image and then detects the high contrast image pixels which usually lie around the text stroke boundary. The document text is then segmented by using local thresholds that are estimated from the detected high contrast pixels within a local neighborhood window. The proposed technique has been tested over the dataset that is used in the recent Document Image Binarization Contest (DIBCO) 2009. Experiments show its superior performance. Copyright 2010 ACM.|
|Source Title:||ACM International Conference Proceeding Series|
|Appears in Collections:||Staff Publications|
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