Recognition of Bengali Handwritten Characters Using Skeletal Convexity and Dynamic Programming
19 Feb 2011-pp 265-268
TL;DR: This paper presents a novel handwritten character recognition method based on the structural shape of a character irrespective of the viewing direction on the 2D plane, and preliminary results demonstrate the efficacy of this approach.
Abstract: The main challenge in recognizing handwritten characters is to handle large-scale shape variations in the handwriting of different individuals. In this paper, we present a novel handwritten character recognition method based on the structural shape of a character irrespective of the viewing direction on the 2D plane. Structural shape of a character is described by different skeletal convexities of character strokes. Such skeletal convexity acts as an invariant feature for character recognition. Longest common subsequence matching is used for recognition. We have tested out method on a benchmark dataset of handwritten Bengali character images. Preliminary results demonstrate the efficacy of our approach.
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TL;DR: This article is intended to provide a history of the project and some of the key events leading up to and during the development of the plan.
Abstract: Article history: Received: 23 January, 2020 Accepted: 26 February, 2020 Online: 16 March, 2020
Cites methods from "Recognition of Bengali Handwritten ..."
...[3] used skeletal concavity/convexity of characters along two directions with a recognition accuracy of 60....
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01 Sep 2017
TL;DR: A new method of feature extraction of printed Bengali alphabets that can be used for Optical Character Recognition or Classification and keeps in mind that the feature space for an alphabet do not get very bigger and so the way to real time recognition becomes much easier.
Abstract: This work proposes a new method of feature extraction of printed Bengali alphabets that can be used for Optical Character Recognition or Classification. This work proposes some specific features and the method that can be used to detect and extract the features that can be used to effectively distinguish between two characters. This method also keeps in mind that the feature space for an alphabet do not get very bigger and so the way to real time recognition becomes much easier. A specific number system has been used to represent the presence or absence of each feature that can be used later in the recognition phase for grouping or classification.
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01 Jan 1990TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Abstract: From the Publisher:
The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures. Like the first edition,this text can also be used for self-study by technical professionals since it discusses engineering issues in algorithm design as well as the mathematical aspects.
In its new edition,Introduction to Algorithms continues to provide a comprehensive introduction to the modern study of algorithms. The revision has been updated to reflect changes in the years since the book's original publication. New chapters on the role of algorithms in computing and on probabilistic analysis and randomized algorithms have been included. Sections throughout the book have been rewritten for increased clarity,and material has been added wherever a fuller explanation has seemed useful or new information warrants expanded coverage.
As in the classic first edition,this new edition of Introduction to Algorithms presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers. Further,the algorithms are presented in pseudocode to make the book easily accessible to students from all programming language backgrounds.
Each chapter presents an algorithm,a design technique,an application area,or a related topic. The chapters are not dependent on one another,so the instructor can organize his or her use of the book in the way that best suits the course's needs. Additionally,the new edition offers a 25% increase over the first edition in the number of problems,giving the book 155 problems and over 900 exercises thatreinforcethe concepts the students are learning.
21,651 citations
TL;DR: In this article, a language similar to logo is used to draw geometric pictures using this language and programs are developed to draw geometrical pictures using it, which is similar to the one we use in this paper.
Abstract: The primary purpose of a programming language is to assist the programmer in the practice of her art. Each language is either designed for a class of problems or supports a different style of programming. In other words, a programming language turns the computer into a ‘virtual machine’ whose features and capabilities are unlimited. In this article, we illustrate these aspects through a language similar tologo. Programs are developed to draw geometric pictures using this language.
5,749 citations
TL;DR: A comprehensive survey of thinning methodologies, including iterative deletion of pixels and nonpixel-based methods, is presented and the relationships among them are explored.
Abstract: A comprehensive survey of thinning methodologies is presented. A wide range of thinning algorithms, including iterative deletion of pixels and nonpixel-based methods, is covered. Skeletonization algorithms based on medial axis and other distance transforms are not considered. An overview of the iterative thinning process and the pixel-deletion criteria needed to preserve the connectivity of the image pattern is given first. Thinning algorithms are then considered in terms of these criteria and their modes of operation. Nonpixel-based methods that usually produce a center line of the pattern directly in one pass without examining all the individual pixels are discussed. The algorithms are considered in great detail and scope, and the relationships among them are explored. >
1,827 citations
TL;DR: A review of the OCR work done on Indian language scripts and the scope of future work and further steps needed for Indian script OCR development is presented.
592 citations
"Recognition of Bengali Handwritten ..." refers methods in this paper
...To improve the recognition performance, many feature selection and extraction methods are reported for Indian languages [1]....
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