Holistic word recognition attempts to recognize the entire word image as a single pattern. In general, it performs better than segmentation based word recognition model for known, fixed and small sized lexicon. The present work deals with recognition of handwritten words in Hindi in holistic way. Features like area, aspect ratio, density, pixel ratio, longest run, centroid and projection length...

Word level training refers to the process of learning the parameters of a word recognition system based on word level criteria functions. Previously, researchers trained lexicon-driven handwritten word recognition systems at the character level individually. These systems generally use statistical or neural based character recognizers to produce character level confidence scores. In the case of...

Handwritten Word Recognition is an important problem of Pattern Recognition. Online handwritten recognition system for Devanagari words is still in developing stage and becoming challenging due to the large complexity involvement. In India, more than 300 million people use Devanagari script for documentation. There has been a significant improvement in the research related to the recognition of...

This paper presents a novel holistic technique for classifying Arabic handwritten text documents. The classification 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 structural and statistical features are extracted from these connected ...

Over several years lot of research has been done in handwritten word recognition but yet need for higher recognition rate still exist. In this paper we have proposed a method that performs preprocessing steps like skew and slant correction. It uses best structural features for feature extraction .Euclidean distance method is applied for classification that produces single matching word having m...

High accuracy character recognition techniques can provide useful information for segmentation-based handwritten word recognition systems. This research describes neural network-based techniques for segmented character recognition that may be applied to the segmentation and recognition components of an off-line handwritten word recognition system. Two neural architectures along with two differe...

ÐThe Holistic paradigm in handwritten word recognition treats the word as a single, indivisible entity and attempts to recognize words from their overall shape, as opposed to their character contents. In this survey, we have attempted to take a fresh look at the potential role of the Holistic paradigm in handwritten word recognition. The survey begins with an overview of studies of reading whic...

Automatic recognition of historical handwritten manuscripts is a daunting task due to paper degradation over time. Recognition-free retrieval or word spotting is popularly used for information retrieval and digitization of the historical handwritten documents. However, the performance of word spotting algorithms depends heavily on feature detection and representation methods. Although there exi...