scholarly journals Usability Evaluation of Randomly Generated Fonts for Bubble Captcha

MENDEL ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 143-150
Author(s):  
Ondrej Bostik ◽  
Karel Horak ◽  
Jan Klecka
Keyword(s):  
Web Services ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Human Perception ◽  
Turing Test ◽  
Usability Evaluation ◽  
Wide Spread ◽  
Optical Character ◽  
Ongoing Work ◽  
The Web

A Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), is the wide-spread concept of systems suited to secure the web services from automated SPAM scripts. The most common CAPTCHA systems benefit from imperfections of Optical Character Recognition algorithms. This paper presents our ongoing work focused on the development of a new CAPTCHA scheme based on a human perception. The goal of this work is to evaluate the usability of randomly generated fonts used in Bubble Captcha scheme with both humans and OCR classifiers.

Polarity Identification for Handwritten Text in Multilingual Documents Using Open Source Optical Character Recognition Tools

2020 ◽  
Vol 17 (9) ◽  
pp. 4045-4049
Author(s):  
C. P. Chandrika ◽  
Jagadish S. Kallimani
Keyword(s):  
Web Services ◽  
Open Source ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Customer Reviews ◽  
Optical Character ◽  
Handwritten Text ◽  
Amazon Web Services ◽  
Rest Api

Sentimental analysis is a prerequisite for many applications. We propose a model which scans handwritten text in English and Kannada languages by a CamScanner and then translated into editable text by using various Open Source Optical Character Recognition tools. The performances of different OCRs are analyzed and tabulated. Sentimental analysis is performed on the statements written in both English and Kannada languages using Wordnet, Algorithmia Rest API and local dictionaries and we have obtained the satisfied results. The same sentimental analysis module is also applied on customer reviews for the mobile product and reviews are taken from Amazon Web Services. The opinion of the customer about the product can be identified correctly.

scholarly journals Bubble Captcha - A Start of the New Direction of Text Captcha Scheme Development

MENDEL ◽  
2017 ◽  
Vol 23 (1) ◽  
pp. 57-64 ◽  
Author(s):  
Ondrej Bostik ◽  
Karel Horak ◽  
Jan Klecka
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Turing Test ◽  
Simple Approach ◽  
Internet Services ◽  
Malicious Activity ◽  
Optical Character ◽  
Recognition Algorithms ◽  
The World ◽  
Human Capability

CAPTCHA, A Completely Automated Public Turing test to tell Computers and Humans Apart, iswell-known system widely used in all sorts of internet services around the world designated to secure the webfrom an automatic malicious activity. For almost two decades almost every system utilize a simple approach tothis problem containing a transcription of distorted letters from image to a text eld. The ground idea is to useimperfection of Optical Character Recognition algorithms against the computers. The development of OpticalCharacter recognition algorithms leads only to state, where the CAPTCHA schemes become more complex andhuman users have a great di culty with the transcription.This paper aims to present a new way of development of CAPTCHA schemes based more a human perception.The goal of this work is to implement new Captcha scheme and assess human capability to read unusual fontsnewer seen before.

scholarly journals A usability evaluation of an interactive application for halal products using optical character recognition and augmented reality technologies

2017 ◽  
Author(s):  
Meng Chun Lam ◽  
Siti Soleha Muhammad Nizam ◽  
Haslina Arshad ◽  
Saidatul A’isyah Ahmad Shukri ◽  
Nurhazarifah Che Hashim ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Usability Evaluation ◽  
Optical Character ◽  
Interactive Application

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.

CNN-based Rain Reduction in Street View Images

2020 ◽  
Vol 2020 (1) ◽  
pp. 78-81
Author(s):  
Simone Zini ◽  
Simone Bianco ◽  
Raimondo Schettini
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
State Of The Art ◽  
Weather Conditions ◽  
Specific Interest ◽  
Optical Character ◽  
Street View ◽  
In The Wild ◽  
Bad Weather ◽  
Detection And Recognition

Rain removal from pictures taken under bad weather conditions is a challenging task that aims to improve the overall quality and visibility of a scene. The enhanced images usually constitute the input for subsequent Computer Vision tasks such as detection and classification. In this paper, we present a Convolutional Neural Network, based on the Pix2Pix model, for rain streaks removal from images, with specific interest in evaluating the results of the processing operation with respect to the Optical Character Recognition (OCR) task. In particular, we present a way to generate a rainy version of the Street View Text Dataset (R-SVTD) for "text detection and recognition" evaluation in bad weather conditions. Experimental results on this dataset show that our model is able to outperform the state of the art in terms of two commonly used image quality metrics, and that it is capable to improve the performances of an OCR model to detect and recognise text in the wild.

Pengantar dan Survey Tentang Optical Music Recognition

2014 ◽  
Vol 6 (1) ◽  
pp. 36-39
Author(s):  
Kevin Purwito
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Optical Music Recognition ◽  
Optical Character ◽  
Digital Format ◽  
Music Recognition ◽  
Index Terms ◽  
The Many ◽  
Further Development ◽  
Music Symbol

This paper describes about one of the many extension of Optical Character Recognition (OCR), that is Optical Music Recognition (OMR). OMR is used to recognize musical sheets into digital format, such as MIDI or MusicXML. There are many musical symbols that usually used in musical sheets and therefore needs to be recognized by OMR, such as staff; treble, bass, alto and tenor clef; sharp, flat and natural; beams, staccato, staccatissimo, dynamic, tenuto, marcato, stopped note, harmonic and fermata; notes; rests; ties and slurs; and also mordent and turn. OMR usually has four main processes, namely Preprocessing, Music Symbol Recognition, Musical Notation Reconstruction and Final Representation Construction. Each of those four main processes uses different methods and algorithms and each of those processes still needs further development and research. There are already many application that uses OMR to date, but none gives the perfect result. Therefore, besides the development and research for each OMR process, there is also a need to a development and research for combined recognizer, that combines the results from different OMR application to increase the final result’s accuracy. Index Terms—Music, optical character recognition, optical music recognition, musical symbol, image processing, combined recognizer  

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