The encoding of local features is an essential part for writer identification and writer retrieval. While CNN activations have already been used as local features in related works, the encoding of these features has attracted little attention so far. In this work, we compare the established VLAD encoding with triangulation embedding. We further investigate generalized max pooling as an alternat...

In this paper we present a geometrical correction method of handwritten characters. This normalization method is based on Fourier coefficients of a chain-encoded contour. It is carried out in order to improve the rate and the performance of an Arabic handwritten word recognition system. The recognition is based on the global observation of apparent features associated to key-letters of the reco...

In this paper, Modified Multi-scale Segmentation Network (MMU-SNet) method is proposed for Tamil text recognition. Handwritten texts from digital writing pad notes are used words recognition written through file conversion challenging due to stylus pressure, on glass frictionless surfaces, and being less skilled in short writing, alphabet size, style, carved symbols, orientation angle variation...

In this article, we describe a prototype system for recognition of online handwritten cursive words of Bangla, a script used by more than 200 million people of India and Bangladesh, two neighboring countries of Asia. To the best of our knowledge, in the literature, there does not exist any work on recognition of such online Bangla cursive words. Here, we propose an analytic recognition approach...

This paper presents an Arabic handwritten text recognition system for historical Manuscripts using the Matlab software, the paper is composed from number of stages, the first stage giving a short description of related work in handwritten Arabic recognition systems, the second stage discuss the preprocessing methods which contain of filtering, a certain methods will be applied on samples of dat...

Handwriting has continued to persist as a means of communication and recording information in day-to-day life even with the introduction of new technologies. Given its ubiquity in human transactions, machine recognition of handwriting has practical significance, as in reading handwritten notes in a personal Digital Assistant (PDA), in postal addresses on envelopes, in amounts in bank checks, in...

The segmentation of individual words is a crucial step in several data mining methods for historical handwritten documents. Examples of applications include visual searching for query words (word spotting) and character-by-character text recognition. In this paper, we present a novel method for word segmentation that is adapted from recent advances in computer vision, deep learning and generic ...

Effective segmentation of offline handwritten word images of unconstrained handwritten Bangla script is a challenging problem in Optical Character Recognition (OCR) application. Presence of a continuous horizontal line called ‘Matra’ is an important feature of this script. However, in unconstrained cursive handwriting, Matra can be wavy or discontinuous, makes the problem of segmentation diffic...

In this paper we address the problem of offline Arabic handwriting word recognition. Offline recognition of handwritten words is a difficult task due to the high variability and uncertainty of human writing. The majority of the recent systems are constrained by the size of the lexicon to deal with and the number of writers. In this paper, we propose an approach for multi-writers Arabic handwrit...

One important issue often neglected in the literature on visualword recognition, despite its obvious ecological validity, is how the cognitive system processes handwritten words. Although handscript was the initial and only way of writing/reading until the 15th century, the vast majority of psycholinguistic experiments use spotless printed words in which, unlike in handwriting, letters are phys...