We present a system that classifies pixels in a document image according to marking type such as machine print, handwriting, and noise. A segmenter module first splits an input ...
Abstract. Automatic identification of a script in a given document image facilitates many important applications such as automatic archiving of multilingual documents, searching on...
Gopal Datt Joshi, Saurabh Garg, Jayanthi Sivaswamy
We propose an approach to restore severely degraded
document images using a probabilistic context model. Un-
like traditional approaches that use previously learned
prior models...
Jyotirmoy Banerjee, Anoop M. Namboodiri, C. V. Jaw...
Developing effective content recognition methods for diverse imagery continues to challenge computer vision researchers. We present a new approach for document image content catego...
Guangyu Zhu, Xiaodong Yu, Yi Li, David S. Doermann
A statistical generative model is presented as an alternative to negative selection in anomaly detection of string data. We extend the probabilistic approach to binary classificat...