scholarly journals Angular Symmetric Axis Constellation Model for off-line Odia Handwritten Characters Recognition

2018 ◽  
Vol 7 (3) ◽  
pp. 265
Author(s):  
Pyari Mohan Jena ◽  
Soumya Ranjan Nayak
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Symmetry Axis ◽  
The Novel ◽  
Accuracy Rate ◽  
Recognition Pattern ◽  
Novel Approach ◽  
Machine Readable ◽  
Machine Readable Form ◽  
Recognition Technique

<span>Optical character recognition is one of the emerging research topics in the field of image processing, and it has extensive area of application in pattern recognition. Odia handwritten script is the most research concern area because it has eldest and most likable language in the state of odisha, India. Odia character is a usually handwritten, which was generally occupied by scanner into machine readable form. In this regard several recognition technique have been evolved for variance kind of languages but writing pattern of odia character is just like as curve appearance; Hence it is more difficult for recognition. In this article we have presented the novel approach for Odia character recognition based on the different angle based symmetric axis feature extraction technique which gives high accuracy of recognition pattern. This empirical model generates a unique angle based boundary points on every skeletonised character images. These points are interconnected with each other in order to extract row and column symmetry axis. We extracted feature matrix having mean distance of row, mean angle of row, mean distance of column and mean angle of column from centre of the image to midpoint of the symmetric axis respectively. The system uses a 10 fold validation to the random forest (RF) classifier and SVM for feature matrix. We have considered the standard database on 200 images having each of 47 Odia character and 10 Odia numeric for simulation. As we have noted outcome of simulation of SVM and RF yields 96.3% and 98.2% accuracy rate on NIT Rourkela Odia character database and 88.9% and 93.6% from ISI Kolkata Odia numerical database.</span>

scholarly journals Angular Symmetric Axis Constellation Model for Off-line Odia Handwritten Characters Recognition

2018 ◽  
Vol 7 (2) ◽  
pp. 96
Author(s):  
Pyari Mohan Jena ◽  
Soumya Ranjan Nayak
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Symmetry Axis ◽  
The Novel ◽  
Accuracy Rate ◽  
Recognition Pattern ◽  
Novel Approach ◽  
Machine Readable ◽  
Machine Readable Form ◽  
Recognition Technique

<span>Optical character recognition is one of the emerging research topics in the field of image processing, and it has extensive area of application in pattern recognition. Odia handwritten script is the most research concern area because it has eldest and most likable language in the state of odisha, India. Odia character is a usually handwritten, which was generally occupied by scanner into machine readable form. In this regard several recognition technique have been evolved for variance kind of languages but writing pattern of odia character is just like as curve appearance; Hence it is more difficult for recognition. In this article we have presented the novel approach for Odia character recognition based on the different angle based symmetric axis feature extraction technique which gives high accuracy of recognition pattern. This empirical model generates a unique angle based boundary points on every skeletonised character images. These points are interconnected with each other in order to extract row and column symmetry axis. We extracted feature matrix having mean distance of row, mean angle of row, mean distance of column and mean angle of column from centre of the image to midpoint of the symmetric axis respectively. The system uses a 10 fold validation to the random forest (RF) classifier and SVM for feature matrix. We have considered the standard database on 200 images having each of 47 Odia character and 10 Odia numeric for simulation. As we have noted outcome of simulation of SVM and RF yields 96.3% and 98.2% accuracy rate on NIT Rourkela Odia character database and 88.9% and 93.6% from ISI Kolkata Odia numerical database.</span>

scholarly journals Feature Extraction Techniques Based on Swarm Intelligence in OCR

2019 ◽  
Vol 8 (12) ◽  
pp. 13-19
Keyword(s):  
Feature Extraction ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Feature Vector ◽  
Extraction Techniques ◽  
Optical Character ◽  
Readable Form ◽  
Machine Readable ◽  
Machine Readable Form ◽  
Recognition Technique

Optical Character Recognition is a most recent field in area of pattern recognition and machine learning in last decade. In this article, the suitable techniques are designated for better character recognition in document into machine readable form. It is belonging with Content Based Image Retrieval (CBIR) system, which solve the delinquent of searching images in huge dataset. The recognition technique of handwritten character is not developed efficiently till, because of variations in size, shape, style, slats etc. in writing skill of human being. To overcome such problems, the part of concentration is feature extraction and algorithm that take care of such variation. In this paper independent component analysis is used for extracting features. For feature vector selection particle swarm optimization and firefly algorithms are applied. It is observed that due to distributed neighborhood pixel of an image, the PSO gives better recognition rates.

scholarly journals Corpus Linguistics and Eighteenth Century Collections Online (ECCO)

2021 ◽  
Vol 9 (1) ◽  
pp. 19-34
Author(s):  
Mikko Tolonen ◽  
Eetu Mäkelä ◽  
Ali Ijaz ◽  
Leo Lahti
Keyword(s):  
Eighteenth Century ◽  
Corpus Linguistics ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Historical Source ◽  
Optical Character ◽  
Key Aspects ◽  
Machine Readable ◽  
Machine Readable Form

Eighteenth Century Collections Online (ECCO) is the most comprehensive dataset available in machine-readable form for eighteenth-century printed texts. It plays a crucial role in studies of eighteenth-century language and it has vast potential for corpus linguistics. At the same time, it is an unbalanced corpus that poses a series of different problems. The aim of this paper is to offer a general overview of ECCO for corpus linguistics by analysing, for example, its publication countries and languages. We will also analyse the role of the substantial number of reprints and new editions in the data, discuss genres and the estimates of Optical Character Recognition (OCR) quality. Our conclusion is that whereas ECCO provides a valuable source for corpus linguistics, scholars need to pay attention to historical source criticism. We have highlighted key aspects that need to be taken into consideration when considering its possible uses.

scholarly journals Spatio Partitioning of Character Image for Automatic Recognition of Digits

2019 ◽  
Vol 8 (3) ◽  
pp. 8171-8177
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Fast Response ◽  
Software Systems ◽  
Decision Tree Classifier ◽  
Optical Character ◽  
Tree Classifier ◽  
Spatially Distributed ◽  
Machine Readable ◽  
Machine Readable Form

In the running word, there is growing demand for the software systems to recognize characters in computer system when information is scanned through paper documents as we have number of newspapers and books which are in printed format related to different subjects the current capacity to translate paper documents quickly and accurately into machine readable form using optical character recognition technology augments the opportunities in document searching and storing as well as automated documents processing. A fast response in translating large collections of image-based electronic documents into structured electronics documents is still a problem. As an enhancement to the optical character recognition [1] (OCR) technology, I would like to propose a framework that recognize a printed digits in the character image using “spatio partitioning method”. The proposed system is efficiently recognize the digits from 0 to 9 different font size based on the new concept of feature extraction and which is classified under decision tree classifier, efficiency and time complexity of the proposed system also described. Partitioning is based on the pixel distribution of the character image; the pixel distribution describes the patter of the characters that is by spatially distributed foreground pixel.

A Structured Method for the Recognition of Complex Historical Tables

1997 ◽  
Vol 9 (1-3) ◽  
pp. 58-77
Author(s):  
Vitaly Kliatskine ◽  
Eugene Shchepin ◽  
Gunnar Thorvaldsen ◽  
Konstantin Zingerman ◽  
Valery Lazarev
Keyword(s):  
Nineteenth Century ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Complex Structure ◽  
Source Material ◽  
Historical Sources ◽  
Tax Assessment ◽  
Optical Character ◽  
Algorithmic Model ◽  
Machine Readable

In principle, printed source material should be made machine-readable with systems for Optical Character Recognition, rather than being typed once more. Offthe-shelf commercial OCR programs tend, however, to be inadequate for lists with a complex layout. The tax assessment lists that assess most nineteenth century farms in Norway, constitute one example among a series of valuable sources which can only be interpreted successfully with specially designed OCR software. This paper considers the problems involved in the recognition of material with a complex table structure, outlining a new algorithmic model based on ‘linked hierarchies’. Within the scope of this model, a variety of tables and layouts can be described and recognized. The ‘linked hierarchies’ model has been implemented in the ‘CRIPT’ OCR software system, which successfully reads tables with a complex structure from several different historical sources.

scholarly journals Vision-Based Parking Entry Control System

2018 ◽  
Vol 17 (2) ◽  
pp. 30-34
Author(s):  
Ahmad Ridhwan Wahap ◽  
Shahrulnafiin Saharudin
Keyword(s):  
Control Systems ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Intelligent Transportation System ◽  
Vision System ◽  
Intelligent Transportation ◽  
Vehicle Owner ◽  
Optical Character ◽  
Counting Algorithms ◽  
Recognition Technique

Vision-based control systems are very promising in the Intelligent Transportation System (ITS). This paper proposes a system that use the vision system to control vehicle entry at the bridge gate at a certain facility. The system detects the presence of the car and captures the front car image to proceed to plate recognition process. Vehicle plate region is extracted using the size filtering, image thresholding and object counting algorithms. Optical character recognition technique is used in the recognition module. The result from the recognition module is then compared to the record in the database for information like the vehicle owner name, type of car, etc. The overall system is implemented and simulated in LabVIEW and the performance of recognition is tested on the real image. The system can successfully detect and recognize the plate number with minimum error.

scholarly journals Smart Reader Glass for Blind and Visually Impaired People

2021 ◽  
Author(s):  
S. Anbarasi ◽  
S. Krishnaveni ◽  
R. Aruna ◽  
K. Karpagasaravanakumar
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Cost Effective ◽  
Blind And Visually Impaired ◽  
Novel Technology ◽  
Visually Impaired People ◽  
Impaired People ◽  
User Friendly ◽  
Recognition Technique

Visually impaired people fail to read the text with existing technology. The proposed project targeted to design a spectacle with a camera by which the blind visually impaired people can read whatever they want to read based on contemporary OCR (optical character recognition) technique and text-to-speech (TTS) engines. This proposed smart reader will read any kind of documents like books, magazines and mobiles. People can access this novel technology with blindness and limited vision. The earlier version of the proposed project was developed successfully with mobile reader which had certain drawbacks such as high cost due to the need of android mobile, not user friendly and improper focusing. To overcome these disadvantages, a spectacle type reader with camera is proposed in this project, which will be cost effective and more efficient.

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