Document image binarization is an important step in the document image analysis and recognition pipeline. H-DIBCO 2014 is the International Document Image Binarization Competition which is dedicated to handwritten document images organized in conjunction with ICFHR 2014 conference. The objective of the contest is to identify current advances in handwritten document image binarization using meaningful evaluation performance measures. This paper reports on the contest details including the evaluation measures used as well as the performance of the 7 submitted methods along with a short description of each method.

DIBCO 2013 is the international Document Image Binarization Contest organized in the context of ICDAR 2013 conference. The general objective of the contest is to identify current advances in document image binarization for both machine-printed and handwritten document images using evaluation performance measures that conform to document image analysis and recognition. This paper describes the contest details including the evaluation measures used as well as the performance of the 23 submitted methods along with a short description of each method.

Document image binarization is of great importance in the document image analysis and recognition pipeline since it affects further stages of the recognition process. The evaluation of a binarization method aids in studying its algorithmic behavior, as well as verifying its effectiveness, by providing qualitative and quantitative indication of its performance. This paper addresses a pixel-based binarization evaluation methodology for historical handwritten/machine-printed document images. In the proposed evaluation scheme, the recall and precision evaluation measures are properly modified using a weighting scheme that diminishes any potential evaluation bias. Additional performance metrics of the proposed evaluation scheme consist of the percentage rates of broken and missed text, false alarms, background noise, character enlargement, and merging. Several experiments conducted in comparison with other pixel-based evaluation measures demonstrate the validity of the proposed evaluation scheme.

H-DIBCO 2012 is the International Document Image Binarization Competition which is dedicated to handwritten document images organized in conjunction with ICFHR 2012 conference. The objective of the contest is to identify current advances in handwritten document image binarization using meaningful evaluation performance measures. This paper reports on the contest details including the evaluation measures used as well as the performance of the 24 submitted methods along with a short description of each method.

In this paper we present a binarization technique for textual content in video frames which can be applied in the resulting image of the text detection step aiming in an improved OCR performance. The proposed technique is based on the detection of the text baselines in order to define the main body of the text. The main body of the text is used to detect the stroke width of the characters which will address the two consecutive locally adaptive binarization steps that follow. At the first step, we use different valuation in parameters for the inside and outside area of the main body of the text. To include the thinned or broken binarized parts that may exist outside the main text body, convex hull analysis is performed so that the entire text body is considered. At the second step, binarization is performed with different valuation in parameters for the inside and outside area of the entire text body. The effectiveness of the proposed technique is demonstrated by both qualitative and OCR-based evaluation.

DIBCO 2011 is the International Document Image Binarization Contest organized in the context of ICDAR 2011 conference. The general objective of the contest is to identify current advances in document image binarization for both machine-printed and handwritten document images using evaluation performance measures that conform to document image analysis and recognition. This paper describes the contest details including the evaluation measures used as well as the performance of the 18 submitted methods along with a short description of each method.

H-DIBCO 2010 is the International Document Image Binarization Contest which is dedicated to handwritten document images organized in conjunction with ICFHR 2010 conference. The general objective of the contest is to identify current advances in handwritten document image binarization using meaningful evaluation performance measures. This paper reports on the contest details including the evaluation measures used as well as the performance of the 17 submitted methods along with a short description of each method.

DIBCO 2009 is the first International Document Image Binarization Contest organized in the context of ICDAR 2009 conference. The general objective of the contest is to identify current advances in document image binarization using established evaluation performance measures. This paper describes the contest details including the evaluation measures used as well as the performance of the 43 submitted methods along with a short description of each method.

In this paper, a new document image binarization technique is presented, as an improved version of the state-of-the-art adaptive logical level technique (ALLT). The original ALLT depends on fixed windows to extract essential features such as the character stroke width. Since characters with several different stroke widths may exist within a region, this can lead to erroneous results. In our approach, we use local adaptive binarization as a guide to our adaptive stroke width detection. The skeleton and the contour points of the binarization output are combined to identify locally the stroke width. Additionally, we introduce an adaptive local parameter ldquobetardquo that enhances the characters and improves the overall performance. In this way, we achieve more accurate binarization results in both handwritten and printed documents with a particular focus on degraded historical documents. Experimental results prove the effectiveness of the proposed technique compared to other state-of-the-art methodologies.

Evaluation of document image binarization techniques is a tedious task that is mainly performedby a human expert or by involving an OCR engine. This paper presents an objective evaluation methodology for document image binarization techniques that aims to reduce the human involvement in the ground truth construction and consecutive testing. A skeletonized ground truth image is produced by the user following a semi-automatic procedure. The estimated ground truth image can aid in evaluating the binarization result in terms of recall and precision as well as to further analyze the result by calculating broken and missing text, deformations and false alarms. A detailed description of the methodology along with a benchmarking of the six (6) most promising state-of-the-art binarization algorithms based on the proposed methodology is presented.

Non-linear warping appears in document images when captured by a digital camera or a scanner, especially in the case that these documents are digitized bounded volumes. Arbitrarily warped documents may have several slope changes along the text lines as well as along the words of the same text line. In this paper, a novel segmentation based technique for efficient restoration of arbitrarily warped document images is presented. The proposed technique recovers the documents relying upon (i) text lines and words detection using a novel segmentation technique appropriate for warped documents, (ii) a first draft binary image de-warping based on word rotation and translation according to upper and lower word baselines, and (Hi) a recovery of the original warped image guided by the draft binary image de-warping result. Experimental results on several arbitrarily warped documents prove the effectiveness of the proposed technique.