Users are still waiting for accurate optical character recognition solutions for Arabic handwritten scripts. This research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic letters. Depending on their position in the word, Arabic letters are drawn in four forms: Isolated, Initial, Medial, and Final. The principal component analysis...

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...

An assembly neural network model is described. The network is artificially partitioned into several sub-networks according to the number of classes that the network has to recognize. In the process of primary learning Hebb's neural assemblies are formed in the sub-networks by means of modification of connections' weights. Then, a differentiation process is executed which significantly improves ...

Segmentation of handwritten input into individual characters is a crucial step in many connected handwriting recognition systems. This paper describes a segmentation algorithm for letters in Roman alphabets, curved pre-stroke cut (CPSC) segmentation. The CPSC algorithm evaluates large set of curved cuts through the image of the input string using dynamic programming and selects a small “optimal...

Sargur N. Srihari & Rohini K. Srihari State University of New York at Bu alo, New York, USA The written form of language is contained in printed documents, such as newspapers, magazines and books, and in handwritten matter, such as found in notebooks and personal letters. Given the importance of written language in human transactions, its automatic recognition has practical signi cance. This ov...

The need for accessing information through the web and other kind of distributed media makes it mandatory to convert almost every kind of document to a digital representation. However, there are many documents that were created long time ago and currently, in the best cases, only scanned images of them are available, when a digital transcription of their content is needed. For such reason, libr...

For many years ago, handwriting is a challenger interest, both online and off line recognition of the handwriting are largely presented in literature. Latin script studies were largely presented using UNIPEN or IRONOFF databases. But Arabic studies were poorly presented in literature because there are no common Arabic d...

In this paper we present a survey of the literature on Arabic writer identification scheme and up-to date techniques employed in identification. The paper begins with an overview of the various writer identification schemes in Arabic and Persian languages. After that, an attempt is made to describe the complex character of Arabic strokes. Previous studies have used a number of Arabic datasets c...

In this paper, we present a method for segmenting Arabic handwritten documents into text lines and words. Text line segmentation is addressed by a well-known technique, the horizontal projection profile, in which autocorrelation is used to enhance the self similarity of this profile. This technique promotes the estimation of text line spacing. Word extraction is based on an adaptation of a know...