To take care of variability involved in the writing style of different individuals a novel approach has been proposed in this article to segment unconstrained handwritten Bangla words into characters. Online handwriting recognition refers to the problem of interpretation of handwriting input captured as a stream of pen positions using a digitizer or other pen position sensor. For online recogni...

The Sinhala script, which is generally with round characters, is unique among other Brahmi-descended scripts and is used by 70% of the 18 million populations in Sri Lanka. There has been no published research on the cursive unconstrained Sinhala handwriting recognition. This paper proposes vital preprocessing stages, which are categorized under thresholding, noise removal, skew detection and co...

We propose a method for increasing word recognition accuracies by correcting the output of a handwriting recognition system. We treat the handwriting recognizer as a black-box, such that there is no access to its internals. This enables us to keep our algorithm general and independent of any particular system. We use a novel method for correcting the output based on a direct “phrase-based” syst...

The issue of handwritten character recognition is still a big challenge to the scientific community. Several approaches to address this challenge have been attempted in the last years, mostly focusing on the English pre-printed or handwritten characters space. Thus, the need to attempt a research related to Arabic handwritten text recognition. Algorithms based on neural networks have proved to ...

Sequence-to-sequence models have recently become very popular for tackling handwritten word recognition problems. However, how to effectively integrate an external language model into such recognizer is still a challenging problem. The main challenge while training deal with the corpus which usually different one used system. Thus, bias between both corpora leads incorrectness on transcriptions...

This paper presents an automatic segmentation scheme for cursive handwritten text lines using the transcriptions of the text lines and a hidden Markov model (HMM) based recognition system. The segmentation scheme has been developed and tested on the IAM database that contains offline images of cursively handwritten English text. The original version of this database contains ground truth for co...

There are immense efforts to design a complete OCR for most of the world’s leading languages, however, multilingual documents either of handwritten or of printed form. As a united attempt, Unicode based OCRs were studied mostly with some positive outcomes, despite the fact that a large character set slows down the recognition significantly. In this paper, we come out with a method to classify w...

Yann Le Cun AT&T Bell Labs Holmdel NJ 07733 We introduce a new approach for on-line recognition of handwritten words written in unconstrained mixed style. The preprocessor performs a word-level normalization by fitting a model of the word structure using the EM algorithm. Words are then coded into low resolution "annotated images" where each pixel contains information about trajectory direction...

We introduce a new approach for on-line recognition of handwritten words written in unconstrained mixed style. The preprocessor performs a word-level normalization by fitting a model of the word structure using the EM algorithm. Words are then coded into low resolution "annotated images" where each pixel contains information about trajectory direction and curvature. The recognizer is a convolut...