HMM has been used successfully to model speech and online signature in the past two decades. The success has been attributed to the fact that these biometric traits have time reference. Only few HMM based offline signature recognition systems have be developed because offline signature lack time reference. This paper presents a recognition system for offline signatures using Discrete Cosine Tra...

Human writing is highly variable and inconsistent, and this makes the offline recognition of handwritten words extremely challenging. This paper describes a novel approach that can be employed for the offline recognition of handwritten Arabic words. Through conceptualizing each word as single, inseparable objects, the proposed approach aims to recognize words in accordance with their complete s...

Support Vector Machines (SVMs) have successfully been used in recognizing printed characters. In the present work, we have used this classification technique to recognize handwritten characters. Recognition of handwritten characters is a difficult task owing to various writing styles of individuals. A scheme for offline handwritten Gurmukhi character recognition based on SVMs is presented in th...

Handwritten signature is the most widely accepted biometric for identity verification. To facilitate objective evaluation and comparison of algorithms in the field of automatic handwritten signature verification, we organized the First International Signature Verification Competition (SVC2004) recently as a step towards establishing common benchmark databases and benchmarking rules. For each of...

This thesis investigates ensemble methods for offline recognition of English handwritten text lines. Multiple recognisers are automatically generated from a single base recognition system. Combining the output of these multiple recognisers provides the final ensemble result. The underlying recognisers are based on hidden Markov models. One model is built for each character. Based on the lexicon...

Handwritten Character Recognition (HCR) is one of the challenging processes. Automatic recognition of handwritten characters is a difficult task. In this paper, we have presented a scheme for offline handwritten Gurmukhi character recognition based on CNN classifier. The system first prepares a skeleton of the character, so that feature information about the character is extracted. CNN based ap...

In this paper we describe a database that consists of offline handwritten Spanish sentences from four different subtasks. The database includes 1 500 forms produced by the same number of writers. A total of around 100 000 word instances out of a vocabulary of around 3 300 words occur in the collection. This database is intended to be used for offline handwriting recognition tasks. However, this...

In handwritten character recognition, benchmark database plays an important role in evaluating the performance of various algorithms and the results obtained by various researchers. In Devnagari script, there is lack of such official benchmark. This paper focuses on the generation of offline benchmark database for Devnagari handwritten numerals and characters. The present work generated 5137 an...

Public key cryptography usually is computationally more expensive than symmetric key systems. Due to this low power or resource constrained devices cannot make use of public key cryptosystems easily. There is a need for high security in these devices since many of these devices perform complex tasks which includes interaction with third party cloud infrastructures. These cloud infrastructures a...

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...