Evaluation of binarization methods for document images

Trier, Øivind Due; Taxt, Torfinn

doi:10.1109/34.368197

Cited by 341 publications

(142 citation statements)

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“…Choice of threshold selection method is the central step in the design of any adaptive thresholding algorithm, and many approaches have been put forward as suitable for use in the binarisation of line drawing images [1][2][3][4][5][6][7][8][9]. Most work from a grey level histogram of some image area, assuming the grey level distribution to comprise two normally distributed components; one centred on plain (white) paper and the other on inked (black) regions.…”

Section: Threshold Selection For Line Drawing Interpretationmentioning

confidence: 99%

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Thresholding Images of Line Drawings with Hysteresis

Pridmore

2002

Lecture Notes in Computer Science

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Abstract. John Canny's two-level thresholding with hysteresis is now a de facto standard in edge detection. The method consistently outperforms single threshold techniques and is simple to use, but relies on edge detection operators' ability to produce thin input data. To date, thresholding with hysteresis has only been applicable to thick data such as line drawings by top-down systems using a priori knowledge of image content to specify the pixel tracks to be considered. We present, and discuss within the context of line drawing interpretation, a morphological implementation of thresholding with hysteresis that requires only simple thresholding and idempotent dilation and which is applicable to thick data. Initial experiments with the technique are described. A more complete evaluation and formal comparison of the performance of the proposed algorithm with alternative line drawing binarisation methods is underway and will be the subject of a future report.

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Section: Threshold Selection For Line Drawing Interpretationmentioning

confidence: 99%

“…Many thresholding schemes have been proposed [1][2][3][4][5][6], Static, adaptive thresholding methods are the most commonly used in line drawing interpretation. A threshold value is defined as a function of (only) the grey level distribution of a local image region.…”

Section: Introductionmentioning

confidence: 99%

Thresholding Images of Line Drawings with Hysteresis

Pridmore

2002

Lecture Notes in Computer Science

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“…7.1.3), a fixed threshold may lead to gross errors in some situations. Adaptive binarization [27] would most likely improve results, but at a heavier computational cost. This is, in fact, one of the principal advantage of using color markers: robust detection of carefully chosen color patterns is achievable with very few operations per pixel under any illuminant.…”

Section: Processing Timementioning

confidence: 99%

Robust real-time detection of multi-color markers on a cell phone

Bagherinia

Manduchi

2011

J Real-Time Image Proc

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We describe a fast algorithm to detect special multi-color markers with a camera cell phone. These color markers can be used for environmental labeling, for example, as a wayfinding aid for persons with visual impairment. Using a cascade of elemental detectors, robust detection is achieved at an extremely low computational cost. We also introduce a strategy to select surfaces for the marker that ensure very low specular reflection, thus facilitating color-based recognition.

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“…It is obvious that differ-ent values of the PS lead to different binarization results, which means that there is not a set of proper PS values for all types of document images. This has already proved by many evaluations that have been made so far [24][25][26][27]. Therefore, for every technique, to achieve the best binarization result the proper PS values must initially be estimated.…”

Section: Introductionmentioning

confidence: 99%