In document image analysis, segmentation is the task that identifies the regions of a
document. The increasing number of applications of document analysis requires a good …

Text detection in natural scene images is an important prerequisite for many content-based
image analysis tasks, while most current research efforts only focus on horizontal or near …

Providing computers with the ability to process handwriting is both important and
challenging, since many difficulties (eg, different writing styles, alphabets, languages, etc.) …

Many researchers have observed that TCP's congestion control mechanisms can lead to
bursty traffic flows on modern high-speed networks, with a negative impact on overall …

The binarization of degraded document images is a challenging problem in terms of
document analysis. Binarization is a classification process in which intra-image pixels are …

Document image enhancement and binarization methods are often used to improve the
accuracy and efficiency of document image analysis tasks such as text recognition …

The cBAD competition aims at benchmarking state-of-the-art baseline detection algorithms.
It is in line with previous competitions such as the ICDAR 2013 Handwriting Segmentation …

Proper recognition of complex-shaped handwritten compound characters is still a big
challenge for Bangla OCR systems. In this paper, we propose a novel shape decomposition …

We present a learning-based method for handwritten text line segmentation in document
images. Our approach relies on a variant of deep fully convolutional networks (FCNs) with …

Text line detection is crucial for any application associated with Automatic Text Recognition
or Keyword Spotting. Modern algorithms perform good on well-established datasets since …