There are many ways to recognize the identity of individuals and authenticate them. Recognition and authentication of individuals with the help of their handwriting is regarded as a research topic in recent years. It is widely used in the field of security, legal, access control and financial activities. This article tries to examines the identification and authentication of individuals in Pers...

A good Arabic handwritten recognition system must consider the characteristics of Arabic letters which can be explicit such as the presence of diacritics or implicit such as the baseline information (a virtual line on which cursive text are aligned and/join). In order to find an adequate method of features extraction, we have taken into consideration the nature of the Arabic characters. The pap...

Optical character recognition (OCR) computer systems are widely used for of car license plates, enabling visually impaired people to work with written information, etc. One the current areas OCR problems is handwritten characters. This study proposes approaches construction combined models using simple and ensemble learning letters Azerbaijani language. The built proposed utilized several class...

-This review paper deals with a review of the optical character recognition using the Matlab software. OCR or optical character recognition is the process of converting scanned images of machine-printed or handwritten text (numerals, letters, and symbols) into a computer-processable format; also known as optical character recognition (OCR). A typical OCR system contains three logical components...

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...

Abstract. We propose a new method for natural writing recognition that utilizes geometric features of letters. The paper deals with recognition of isolated handwritten characters using an artificial neural network. As a result of the geometrical analysis realized, graphical representations of recognized characters are obtained in the form of pattern descriptions of isolated characters. The radi...

We apply confidence-scoring techniques to verify the output of an off-line handwritten-character recognizer. We evaluate a variety of scoring functions, including likelihood ratios and estimated posterior probabilities of correctness, in a post-processing mode, to generate confidence scores. Using the post-processor in conjunction with a neural-netbased recognizer, on mixed-case letters, receiv...

In this paper, a method for analytic handwritten word recognition based on causal Markov random fields is described. The words models are HMMs where each state corresponds to a letter; each letter is modelled by a NSHP-HMM (Markov field). Global models are build dynamically, and used for recognition and learning with the Baum-Welch algorithm. Learning of letter and word models is made using the...

Artificial Neural Network (ANN) s has widely been used for recognition of optically scanned character, which partially emulates human thinking in the domain of the Artificial Intelligence. But prior to recognition, it is necessary to segment the character from the text to sentences, words etc. Segmentation of words into individual letters has been one of the major problems in handwriting recogn...