Writer adaptation or specialization is the adjustment of handwriting recognition algorithms to a specific writer’s style of handwriting. Such adjustment yields significantly improved recognition rates over counterpart general recognition algorithms. We present a discussion of a method of prototype integration for writer adaptation and evaluate the results on English and Arabic datasets. The wri...

OFFLINE handwriting recognition is the task of determining what letters or words are present in a digital image of handwritten text. It is of significant benefit to man-machine communication and can assist in the automatic processing of handwritten documents. It is a subtask of Optical Character Recognition (OCR), whose domain can be machine-print or handwriting but is more commonly machine-pri...

Abstract Handwritten text recognition systems interpret the scanned script images as composed of letters. In this paper, efficient offline methods using fuzzy degrees, well interval degrees type-2, are proposed to recognize letters beforehand decomposed into strokes. For such strokes, first stage used create a set hypotheses whether group strokes matches letter or digit patterns. Subsequently, ...

standardizing persian alphabet letters in pcs, note books and cell phones is an important issue in persian writing. diversity of letters assigned to a given key as well as inappropriateness of the assigned letters to keys in relation to the frequency of letters are the most important issues for the iranians using persian keyboards. although the standard persian keyboard has been organized in a ...

Despite the growing growth of technology, handwritten signature has been selected as the first option between biometrics by users. In this paper, a new methodology for offline handwritten signature verification and recognition based on the Shearlet transform and transfer learning is proposed. Since, a large percentage of handwritten signatures are composed of curves and the performance of a sig...

In this paper, extracted word features have been used toward offline detection of Persian handwritten words. This has been done using fourteen features in Persian word structure. In this method after required pre-processing, numbers and location of dots versus base line are extracted then the word becomes thin and the feature extraction stage starts. In this stage the words are detected by usin...

In this paper a binary decision tree, based on Neural Networks, Support Vector Machine and K-Nearest Neighbor is employed and presented for recognition of Persian handwritten isolated digits and characters. In the proposed method, a part of the training data is divided into two clustersusing a clustering algorithm, and this process continues until each subtree reaches clusters with optimum clus...

Huge amounts of handwritten historical documents are being published by digital libraries world wide. However, for these raw digital images to be really useful, they need to be annotated with informative content. State-of-the-art Handwritten Text Recognition (HTR) approaches require an impressive training effort by expert paleographers. Our contribution is a scalable, end-to-end transcription w...