Automatic image analysis is a crucial component of many intelligent systems designed for
high-level understanding of documents. Most document image understanding systems are …

In this era of digitization, most hardcopy documents are being transformed into digital
formats. In the process of transformation, large quantities of documents are stored and …

Image processing plays an important role in various medical applications to support the
computerized disease examination. Brain tumor, such as glioma is one of the life threatening …

This paper presents a novel iterative deep learning framework and applies it to document
enhancement and binarization. Unlike the traditional methods that predict the binary label of …

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 …

To maintain the supply of electrical energy, it is necessary that failures in the distribution grid
are identified during inspections of the electrical power system before shutdowns occur. To …

The segmentation of medical images by computational methods has been claimed by the
medical community, which has promoted the development of several algorithms regarding …

In medical domain, diseases in critical internal organs are generally inspected using
invasive/non-invasive imaging techniques. Magnetic resonance imaging (MRI) is one of the …

The human brain is considered to be the anatomical seat of intelligence, comprehensively
supervising conscious and autonomous functions responsible for monitoring and control …

Adaptive binarization methods play a central role in document image processing. In this
work, an adaptive and parameterless generalization of Otsu's method is presented. The …