Fusion of multiple handwritten word recognition techniques is described. A novel borda count for fusion based on ranks and confidence values is proposed. Three techniques with two different conventional segmentation algorithms in conjunction with backpropagation and radial basis function neural networks have been used in this research. Development has taken place a t the University of Missouri ...

It is the problem of computer science that how we detect the handwritten character and word, so it is also the problem in the field of image processing and pattern recognition of computer science. The meaning of handwritten character and word recognition refers to the identification of the characters or word which is written by a human being. Our approach is this, how this problem solved correc...

This paper presents a novel holistic technique for classifying and retrieving Arabic handwritten text documents. The retrieval of Arabic handwritten documents is performed in several steps. First, the Arabic handwritten document images are segmented into words, and then each word is segmented into its connected parts. Second, several features are extracted from these connected parts and then co...

Normalization is a very important step in automatic cursive handwritten word recognition. Based on an offline recognition system for Arabic handwritten words which uses a semi-continuous 1-dimensional HMM recognizer two different feature sets are presented. The dependencies of the feature sets from normalization steps is discussed and their performances are compared using the IFN/ENIT database ...

A format-driven word recognition system is proposed for recognition of handwritten words. Unlike most traditional handwritten word recognizers being given a set of target words as lexicon, we assume that our system is given a set of format descriptions other than lexicon words. Applications of the proposed system include recognition of relatively more important keywords such as postal codes, ti...

Handwritten word recognition is a field of study that has largely been neglected in the psychological literature, despite its prevalence in society. Whereas studies of spoken word recognition almost exclusively employ natural, human voices as stimuli, studies of visual word recognition use synthetic typefaces, thus simplifying the process of word recognition. The current study examined the effe...

Gurumukhi script is used for Punjabi language, which is a two dimensional composition of symbols with connected and disconnected diacritics. Handwritten Gurumukhi script has some complexities like connected, overlapped text lines, words and characters. It is one of the foremost issues for errors during the recognition process. Text segmentation is a challenging job in unconstrained writer indep...

Generating synthetic images is an art which emulates the natural process of image generation in a closest possible manner. In this work, we exploit such a framework for data generation in handwritten domain. We render synthetic data using open source fonts and incorporate data augmentation schemes. As part of this work, we release 9M synthetic handwritten word image corpus which could be useful...

We introduce two data augmentation techniques, which, used with a Resnet-BiLSTM-CTC network, significantly reduce Word Error Rate and Character beyond best-reported results on handwriting text recognition tasks. apply novel that simulates strikethrough (HandWritten Blots) handwritten generation method based printed (StackMix), which proved to be very effective in StackMix uses weakly-supervised...