Document images produced by cameras often have varying degrees of brightness. To resolve the problem, we propose a method that divides an image into several regions and decides what binarization action to take on each region based on the rules that are derived from a learning process. Since each region can allow more than one action to take, we are dealing with a multi-label and multi-class cla...

Digital watermarking has been proposed for the protection of digital medias. This paper presents two watermarking algorithms for binary images. Both algorithms involve a blurring preprocessing and a biased binarization. After the blurring, the first algorithm embeds a watermark by modifying the DC components of the Discrete Cosine Transform (DCT), followed by a biased binarization, and the seco...

Adaptive binarization techniques are proposed for the restoration of degraded documents for WaferficheTMarchival. WaferficheTMis a compact archival solution for long-term preservation of documents in a human-accessible image based format. Bi-level images are preferable for the lithographic fabrication utilized in WaferficheTMproduction. Binarization of degraded documents poses challenges due to...

Binary image is the essential format for document image processing, and the operation of the subsequent steps depends on the quality of the binarization process. The objective of this research is to propose a new binarization method based on adaptive multilayer-information for restoration of degraded historical document images. This paper focuses on degraded Thai historical document images, whi...

In this paper, we propose a novel binarization method for document images produced by cameras. Such images often have varying degrees of brightness and require more careful treatment than merely applying a statistical method to obtain a threshold value. To resolve the problem, the proposed method divides an image into several regions and decides how to binarize each region. The decision rules a...

One of the most important steps of document image processing is binarization. The computational requirements of locally adaptive binarization techniques make them unsuitable for devices with limited computing facilities. In this paper, we have presented a computationally efficient implementation of convolution based locally adaptive binarization techniques keeping the performance comparable to ...

Binarization is often recognized to be one of the most important steps in most high-level image analysis systems, particularly for object recognition. Its precise functioning highly determines the performance of the entire system. According to many researchers, segmentation finishes when the observer's goal is satisfied. Experience has shown that the most effective methods continue to be the it...

Document image binarization is difficult when the image is affected by background noise or nonuniformly illuminated. In this paper, an adaptively method is proposed to address the above problems and thus get expected binarization results. This method begins by defining a filter window length with initialized stroke width, and then transforms the document image into a feature space with Gaussian...

The problem of binarization of gray level images acquired under nonuniform illumination is reconsidered. Yanowitz and Bruckstein proposed to use for image binarization an adaptive threshold surface, determined by interpolation of the image gray levels at points where the image gradient is high. The rationale is that high image gradient indicates probable object edges, and there the image values...

This paper presents a new adaptive binarization technique for degraded hand-held camera-captured document images. The state-of-the-art locally adaptive binarization methods are sensitive to the values of free parameter. This problem is more critical when binarizing degraded camera-captured document images because of distortions like non-uniform illumination, bad shading, blurring, smearing and ...