We propose further improvement of a handwriting recognition method that avoids segmentation while able to recognize words that were never seen before in handwritten form. This met...
Adnan El-Nasan, Sriharsha Veeramachaneni, George N...
In this paper we propose to define a measure of visual similarity to compare different pages in a corpus. This measure is based on the analysis of the visual layout saliency of th...
This paper summarises the achievements of a multidisciplinary Bioinformatics project which has the objective of providing a general mechanism for efficient computerisation of type...
Andy C. Downton, Simon M. Lucas, Gregory Patoulas,...
The increasing availability of high performance, low priced, portable digital imaging devices has created a tremendous opportunity for supplementing traditional scanning for docum...
This paper presents a new technique to improve the combination of classification decisions obtained from local analysis of patterns. Specifically, a genetic algorithm is used to d...
Giovanni Dimauro, Sebastiano Impedovo, Raffaele Mo...
In this paper I will try to explain the nature of document understanding in all of its dimensions. Therefore I will first describe the characteristics of data, knowledge, and info...
Existing skeletonization methods operate directly on the binary image ignoring the gray-level information. In this paper we propose a new method for the skeletonization of handwri...
With an aim to high-level understanding of the mathematical contents in a document image the requirement of math-zone extraction and recognition technique is obvious. In this pape...
S. P. Chowdhury, S. Mandal, Amit Kumar Das, Bhabat...
In this paper, we propose a new character generation method from on-line handwriting recognizers based on Bayesian networks. On-line handwriting recognizers are trained with handw...
In this paper, we propose a Bayesian network framework for explicitly modeling components and their relationships of Korean Hangul characters. A Hangul character is modeled with h...