Analysis of structural features and classification of Gujarati consonants for offline character recognition
نویسنده
چکیده
Wide range of applications and numerous other complexities involved in character recognition (CR) makes it a continuous and open area of research. Feature selection and classification plays major role in achieving higher accuracy for character recognition. In the era of digitization its compelling need to have CR system for regional script. This paper presents analysis of structural features and its classification for consonants of Gujarati script. Each character has certain characteristics which distinguishes it from other characters. Gujarati consonants are analyzed for eight such structural features and on the basis of it characters are categorized into twenty groups. Further Paper proposes decision table to classify characters based on structural features.
منابع مشابه
Structural Feature Extraction to recognize some of the Offline isolated Handwritten Gujarati Characters using Decision Tree Classifier
Large amount of information is prevailing on paper and in an era of digital technology it requires it to store this information in electronic format. Using scanner this information can be digitized. Later any modification in terms of add, editing, removing and searching to it requires a technique or methodology which will identify text from image and convert into ASCII or Unicode. This paper pr...
متن کاملGujarati handwritten numeral optical character reorganization through neural network
This paper deals with an optical character recognition (OCR) system for handwritten Gujarati numbers. One may find so much of work for Indian languages like Hindi, Kannada, Tamil, Bangala, Malayalam, Gurumukhi etc, but Gujarati is a language for which hardly any work is traceable especially for handwritten characters. Here in this work a neural network is proposed for Gujarati handwritten digit...
متن کاملNeural Network Based Recognition System Integrating Feature Extraction and Classification for English Handwritten
Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...
متن کاملStudy and Analysis of various preprocessing approaches to enhance Offline Handwritten Gujarati Numerals for feature extraction
Since last many years Optical character recognition has been an area attracting many researchers. Due to wide range of applications and advancement of digital technology offline and online handwritten character recognition for regional script is becoming fascinated area of research. In any character recognition system feature extraction phase requires input of image which is noise free, binary ...
متن کاملTamil Character Recognition Using Structural Features
In this paper we propose an approach for offline recognition of Tamil characters using their structural features. Structural features are the features that are physically a part of the structure of the character, such as straight lines, arcs, circles, intersections etc. The features used for recognition are the positions of vertical lines, horizontal lines and branching in a character. Some oth...
متن کامل