english alphabet
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Author(s):  
Gulfeshan Parween

Abstract: In this paper, we present a scheme to develop to complete OCR system for printed text English Alphabet of Uppercase of different font and of different sizes so that we can use this system in Banking, Corporate, Legal industry and so on. OCR system consists of different modules like preprocessing, segmentation, feature extraction and recognition. In preprocessing step it is expected to include image gray level conversion, binary conversion etc. After finding out the feature of the segmented characters artificial neural network and can be used for Character Recognition purpose. Efforts have been made to improve the performance of character recognition using artificial neural network techniques. The proposed OCR system is capable of accepting printed document images from a file and implemented using MATLAB R2014a version. Key words: OCR, Printed text, Barcode recognition


Author(s):  
Poonam Bhanudas Abhale

Abstract: Character recognition is a process by which a computer recognizes letters, figures, or symbols and turns them into a digital form that a computer can use. In moment’s terrain character recognition has gained a lot of attention in the field of pattern recognition. Handwritten character recognition is useful in cheque processing in banks, form recycling systems, and numerous further. Character recognition is one of the well- liked and grueling areas of exploration. In the unborn character recognition produce a paperless terrain. In this paper, we describe the detailed study of the being system for handwritten character recognition. We give a literature review on colorful ways used in offline English character recognition. Keywords: Character; Character recognition; Preprocessing; Segmentation; Point birth; Bracket; neural network; Convolution neural network.


Author(s):  
Tai Oluwagbemi
Keyword(s):  

This paper has interrogated the existence of the twenty-six letters in the English alphabet as currently being employed and has concluded that the twenty-six letters have been around for far too long without acceptable addition. The need for expansion has therefore arisen in the light of achieving space conservation when writing and printing hard copies of documents. The paper disagrees with the presentation of the ampersand ‘&’ as the twenty-seventh letter of the English alphabet instead it has proposed being the hybrid resulting from letters ‘s’ and ‘h’ as the twenty-seventh letter. It concluded by recommending the evolution of appropriate letters for other consonant digraphs and trigraphs. This may help in phonological deepening.


2021 ◽  
Vol 10 (5) ◽  
pp. 2557-2565
Author(s):  
Nada Hussain Ali ◽  
Matheel Emad Abdulmunem ◽  
Akbas Ezaldeen Ali

Communication between human beings has several ways, one of the most known and used is speech, both visual and acoustic perceptions sensory are involved, because of that, the speech is considered as a multi-sensory process. Micro contents are a small pieces of information that can be used to boost the learning process. Deep learning is an approach that dives into deep texture layers to learn fine grained details. The convolution neural network (CNN) is a deep learning technique that can be employed as a complementary model with micro learning to hold micro contents to achieve special process. In This paper a proposed model for lip reading system is presented with proposed video dataset. The proposed model receives micro contents (the English alphabet) in video as input and recognize them, the role of CNN deep learning is clearly appeared to perform two tasks, the first one is feature extraction and the second one is the recognition process. The implementation results show an efficient accuracy recognition rate for various video dataset that contains variety lip reader for many persons with age range from 11 to 63 years old, the proposed model gives high recognition rate reach to 98%.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Ki Hyeon Hong ◽  
Un Gu Kang ◽  
Byung Mun Lee

In the field of information security, passwords are a means of authenticating users. Passwords with weak security cannot perform the role of user authentication and personal information protection because confidentiality is easily violated. To ensure confidentiality, it is important to evaluate the strength of the password and choose a very secure password. Due to this fact, security evaluation models for various passwords have been presented. However, existing evaluation models evaluate security based on the English alphabet. Passwords depend on the memory of the user and are closely related to the language or environment used by the user. In this regard, there are limitations in applying the existing security evaluation models to passwords chosen by non-English speakers. We compose a non-English, Korean language-based password dictionary and propose a password security evaluation model based on this for Korean users. In addition, to verify the effectiveness of the proposed model, we conducted experiments to evaluate the security of Korean language-based passwords using a database of passwords that have been actually leaked. As a result, the proposed model showed 99.38% accuracy for Korean language-based leaked passwords. This is superior to the 80.06% accuracy shown by the existing model. In conclusion, the use of the Korean language-based password security evaluation model proposed in this paper will contribute to choosing more secure passwords for Korean language-based sites or users.


Author(s):  
Vishwanath Venkatesh Murthy ◽  
◽  
M Hanumanthappa ◽  

Braille is the language used by visually impaired persons. Braille language comprises of collection of Braille cells which are embossed on a metal plate. Maintaining these bulky metal plates and distributing them to other parts of the world is a challenging task. This paper proposes a new technique of translating the Braille Cells embossed on plate to a natural language English character which can be easily distributed over network to make it globally accessible. Initially Braille documents are scanned, and preprocessing techniques like adaptive histogram and Laplacian filters are applied to augment the dots by eliminating the noise. The existence of dot pattern in every cell is detected with a Threshold and transformed to sequence of Binary matrix. A cell information is translated to 3x2 matrix with binary values of 0’s and 1’s representing absence and presence of dots in a cell. Convolutional Neural Network is used for feature extraction and Classification and Regression Trees (CART) classifier is utilized for recognize the character.


2021 ◽  
Vol 11 (11) ◽  
pp. 5277
Author(s):  
Afnan ◽  
Khan Muhammad ◽  
Noman Khan ◽  
Mi-Young Lee ◽  
Ali Imran ◽  
...  

With the emerging technologies of augmented reality (AR) and virtual reality (VR), the learning process in today’s classroom is much more effective and motivational. Overlaying virtual content into the real world makes learning methods attractive and entertaining for students while performing activities. AR techniques make the learning process easy, and fun as compared to traditional methods. These methods lack focused learning and interactivity between the educational content. To make learning effective, we propose to use handheld marker-based AR technology for primary school students. We developed a set of four applications based on students’ academic course of primary school level for learning purposes of the English alphabet, decimal numbers, animals and birds, and an AR Globe for knowing about different countries around the world. These applications can be played wherever and whenever a user wants without Internet connectivity, subject to the availability of a tablet or mobile device and the required target images. These applications have performance evaluation quizzes (PEQs) for testing students’ learning progress. Our study investigates the effectiveness of AR-based learning materials in terms of learning performance, motivation, attitude, and behavior towards different methods of learning. Our activity results favor AR-based learning techniques where students’ learning motivation and performance are enhanced compared to the non-AR learning methods.


2021 ◽  
Vol 1908 (1) ◽  
pp. 012033
Author(s):  
Hendra Pradibta ◽  
Usman Nurhasan ◽  
Eka Pratitis ◽  
Khusnul Krisiananda
Keyword(s):  

2021 ◽  
pp. 28-45
Author(s):  
Ambalegin Ambalegin

This phonological analysis investigated the English vowel sounds as the central phenomena represented by letters descriptively and qualitatively. It was supported by the theories proposed by Finegan, Hayes, Kreidler, Skandera & Burleigh, Roach and Yule. The method of data collection was observational by identifying the English articulation. The articulatory phonetic identity method was used to analyze the data with competence in differentiating. The Oxford Advanced Learner’s Dictionary was used as a standard form of British pronunciation (Received Pronunciation) to compare the sounds produced and differentiate the English alphabet letters. Some patterns of English vowel pronunciation were found, i.e. <r> positioned as a close syllable lengthens [A:, O:, 3:] and produces schwa, and does so similarly in diphthong. Double semivowels do not perform triphthong. The letters i, u, w and y produce triphthong when they are combined with vowels. Keywords: phonology, Received Pronunciation, vowels


2021 ◽  
Author(s):  
Junwen Zhong ◽  
Wenying Qiu ◽  
Tao Jiang ◽  
Archie Yao ◽  
Zhichun Shao ◽  
...  

Abstract One grand challenge in haptic human-machine interface devices is to electromechanically stimulate sensations on human skins wirelessly by thin and soft patches under a low driving voltage. Here, we propose a soft haptics-feedback system using highly charged, polymeric electret films with the annulus-shape bump contact structure to induce mechanical sensations on volunteers under an applied voltage as low as 5 volts. Together with bendable lithium ion batteries and a flexible circuit board, an untethered stimulation patch is constructed for active operations of at least 2 hours with low power consumptions. As an application example, a “silent haptic communication” system is demonstrated to transmit English alphabet letters via the mechanical beating patterns from a patch onto the fingertip of a receiving volunteer. The analytical model, design principle, and performance characterizations can be applicable for the integrations with other devices in wearable electronics toward various applications, including AR (augmented reality) and VR (virtual reality).


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