A Writer Identification System For Handwritten Malayalam Documents

Handwriting is an acquired tool used for communication of one's observations or feelings. Factors that inuence a person's handwriting not only dependent on the individual's bio-mechanical constraints, handwriting education received, writing instrument, type of paper, background, but also factors like stress, motivation and the purpose of the handwriting. Despite the high variation in a person's handwriting, recent results from different writer identification studies have shown that it possesses sufficient individual traits to be used as an identification method. Handwriting as a behavioral biometric has had the interest of researchers for a long time. But recently it has been enjoying new interest due to an increased need and effort to deal with problems ranging from white-collar crime to terrorist threats. The identification of the writer based on a piece of handwriting is a challenging task for pattern recognition. The main objective of this thesis is to develop a text independent writer identification system for Malayalam Handwriting. The study also extends to developing a framework for online character recognition of Grantha script and Malayalam characters

The Effect of SIFT Features as Content Descriptors in the Context of Automatic Writer Identification in Malayalam Language

The span of writer identification extends to broad domes like digital rights administration, forensic expert decisionmaking systems, and document analysis systems and so on. As the success rate of a writer identification scheme is highly dependent on the features extracted from the documents, the phase of feature extraction and therefore selection is highly significant for writer identification schemes. In this paper, the writer identification in Malayalam language is sought for by utilizing feature extraction technique such as Scale Invariant Features Transform (SIFT).The schemes are tested on a test bed of 280 writers and performance evaluated

Social Justice and Weaker Sections: Role of the Judiciary

The Constitution of India. which has been described by an eminent writer as a "Corner stone of a nation". Has bestowed sufficient thought on the underprivileged. A number of provisions incorporated in it for their benefit tell the tale of statesmanship of the framers of the Constitution. for the vitality of a Constitution depends on the extent to which it affords protection to the under—priveleged. One such laudable provision in the Constitution relates to "weaker sections of the people", which has directed the State to promote with special care the educational and economic interests of such people. Besides. the Constitution has laid great stress on social justice. No comprehensive analysis in a single work seems to have been made so far of the connotations of social justice and the scope of the constitutional safeguards provided in favour of the weaker sections of the people. This thesis is the result of an attempt to analyse the connotations of social justice and the scope of the constitutional provisions made for the benefit of the weaker sections and the role played by the judiciary in this field The weaker sections, which are sought to be covered in this work, are "Backward C1asses". socially and educationally Backward Classes", "Scheduled Castes and Scheduled Tribes" and women. The first two categories of weaker sections have not been defined in the Constitution. So, their meaning and the criteria to determine them have to be gathered from the reports submitted by various Backward Class Commissions and judicial decisions rendered in a number of cases. The main thrust in this work is to understand the meaning and contents of social justice, identify the relevant weaker sections and to examine the extent to which the social justice has been rendered to the said weaker sections. The scope of this thesis is confined to the examination of the role of the judiciary in this field. So, the enquiry has been focussed mainly on the decisions of the judiciary bearing on the subject with a view to assessing the role of the judiciary in rendering social justice meaningful to the weaker sections in particular and to the Indian Society in general.

k-NN based On-Line Handwritten Character recognition system

On-line handwriting recognition has been a frontier area of research for the last few decades under the purview of pattern recognition. Word processing turns to be a vexing experience even if it is with the assistance of an alphanumeric keyboard in Indian languages. A natural solution for this problem is offered through online character recognition. There is abundant literature on the handwriting recognition of western, Chinese and Japanese scripts, but there are very few related to the recognition of Indic script such as Malayalam. This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using K-NN algorithm. It would help in recognizing Malayalam text entered using pen-like devices. A novel feature extraction method, a combination of time domain features and dynamic representation of writing direction along with its curvature is used for recognizing Malayalam characters. This writer independent system gives an excellent accuracy of 98.125% with recognition time of 15-30 milliseconds

Identifying Decisive Features for Distinctive Analysis of Writings in Malayalam

This paper presents a writer identification scheme for Malayalam documents. As the accomplishment rate of a scheme is highly dependent on the features extracted from the documents, the process of feature selection and extraction is highly relevant. The paper describes a set of novel features exclusively for Malayalam language. The features were studied in detail which resulted in a comparative study of all the features. The features are fused to form the feature vector or knowledge vector. This knowledge vector is then used in all the phases of the writer identification scheme. The scheme has been tested on a test bed of 280 writers of which 50 writers having only one page, 215 writers with at least 2 pages and 15 writers with at least 4 pages. To perform a comparative evaluation of the scheme the test is conducted using WD-LBP method also. A recognition rate of around 95% was obtained for the proposed approach

On-Line Handwritten Character Recognition using Kohonen Networks

This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using Kohonen network. It would help in recognizing Malayalam text entered using pen-like devices. It will be more natural and efficient way for users to enter text using a pen than keyboard and mouse. To identify the difference between similar characters in Malayalam a novel feature extraction method has been adopted-a combination of context bitmap and normalized (x, y) coordinates. The system reported an accuracy of 88.75% which is writer independent with a recognition time of 15-32 milliseconds