This review provides a comprehensive view of the field of historical document image
binarization with a focus on the contributions made in the last decade. After the introduction …

This paper presents an effective approach for the local threshold binarization of degraded
document images. We utilize the structural symmetric pixels (SSPs) to calculate the local …

Convolutional neural networks (CNNs) have previously been broadly utilized to binarize
document images. These methods have problems when faced with degraded historical …

Page object detection is crucial for document understanding. Different granularities for
objects can result in different performances. In this study, block level region object detection …

Document image binarization classifies each pixel in an input document image as either
foreground or background under the assumption that the document is pseudo binary in …

Binarization is a fundamental problem in document image analysis systems. Different from
current thresholding techniques, a novel variational model is proposed for noise robust …

In this paper, we propose a novel method for Multispectral document image binarization
(MSdB) through the Non-negative Matrix Factorization (NMF) approach. We propose a three …

Binarization has always been a challenging problem in document image processing
because of various types of degradation. In this paper, we present a nonlinear reaction …

Recognizing texts in video is more complex than in other environments such as scanned
documents. Video texts appear in various colors, unknown fonts and sizes, often affected by …

It is common that historical Tibetan documents belonging to historical collections are poorly
preserved and are prone to degradation processes. This causes many challenges that can …