scholarly journals A Simplified Research for Mathematical Expression Recognition and Its Conversion to Speech

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1033-1038
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Recognition Rate ◽  
Mathematical Expression ◽  
Expression Recognition ◽  
Advanced Mathematics ◽  
Data Set ◽  
Visually Impaired People ◽  
Impaired People

The number of visually impaired people appearing for various examination is increasing every year while on the other hand, there are several blind aspirants who are willing to enrich their knowledge through higher studies. Mathematics is one of the key language (subject) for those who are willing to pursue higher studies in science stream. There is a lot of advanced Braille techniques and OCR to speech conversion software's made available to help visual impaired community to pursue their education but still the number of visually impaired students getting admitted to higher education is less. This is not because most of the data is on paper in the form of books and documents. So, there is a great need to convert information from the physical domain into the digital domain which would help the visually impaired people to read the advanced mathematics text independently. Optical Character Recognition (OCR) systems for mathematics have received considerable attention in recent years due to the tremendous need for the digitization of printed documents. Existing literature reveals that, most of the works concentrated on recognizing handwritten mathematical symbols and some works revolve around complex algorithms. This paper proposes a simple, yet efficient approach to develop an OCR system for mathematics and its conversion to speech. For Mathematical symbol recognition, Skin and Bone algorithm is proposed, which proved its efficiency on a variety of data set. The proposed methodology has been tested on 50 equations comprising various symbols such as integral, differential, square, square root and currently achieving recognition rate of 92%.

scholarly journals Effective Shopping Method for Visually Impaired People using Optical Character Recognition

2019 ◽  
Vol 9 (1) ◽  
pp. 5304-5306
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Detection Method ◽  
General Terms ◽  
Visually Impaired People ◽  
Impaired People ◽  
Text Reading ◽  
Blind User ◽  
Blind Persons

Visual impairment persons are not able to do all works as normal persons especially during purchasing products in supermarket. To help the blind peoples recognise the objects a text reading method is proposed along with the help of camera. A motion detection method is used to detect the presence of the object. The audio instructions about all the objects and their location in supermarket are notified to the blind user that helps them to move freely inside the supermarket. The proposed system aims to make more convenient for the blind persons to purchase in a sophisticated environment. This system also provides easy shopping, consumers time is saved, etc. The implementation of proposed system is done using artificial intelligence and OCR technology. General Terms Visually impaired people, smart shopping, OCR.

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.

Development of Haptic Communication Device for Disabled Persons

2016 ◽  
Author(s):  
Zoltán Szabó ◽  
Eniko T. Enikov
Keyword(s):  
Character Recognition ◽  
Visually Impaired ◽  
Human Subject ◽  
Recognition Performance ◽  
Recognition Rate ◽  
Tactile Perception ◽  
Tactile Display ◽  
Vibrotactile Stimulation ◽  
Visually Impaired People ◽  
Impaired People

With the emergence of augmented and virtual-reality based information delivery technologies the gap between availability of communication devices for visually impaired people and sighted people is emerging. The current study describes a communication tool which provides a reading platform for visually impaired people by means of a haptic display. In this paper the development and human subject study based evaluation of an electromagnetic microactuator-array based virtual tactile display is presented. The actuator array is comprised of a 4 by 5 array of micro voice-coil actuators (tactors) providing vibrotactile stimulation on the user’s fingertip. The size and performance of the actuators is evaluated against the thresholds of human tactile perception. It is demonstrated that a 2.65 mm (diameter) × 4 mm (height) generic tactor is suitable for practical applications in dynamic tactile displays. The maximum force of the actuator was 30 mN generated at current levels of 200 mA. At a stroke of 4.5 mm, the force is reduced to 10 mN. The peak force was generated at a displacement of 1.5 mm. A total of 10 alpha-numeric symbols were displayed to the users via dynamically changing the location of the vibrating point in a predefined sequence, thus creating a tactile perception of continuous curve. Users were asked to sketch out the perceived symbols. Each subject carried out three experiments. The first experiment exposed all subjects to ten different characters. Data obtained from human subject tests suggest that users perceive most shapes accurately, however the existence of jump discontinuities in the flow of presentation of the curves lowers recognition efficiency most likely due to loss of sensation of solid reference point. Characters containing two or more discontinuous lines such as ‘X’ were more difficult to recognize in comparison to those described with a single line such as ‘P’, or ‘Z’. Analysis of the average character recognition rate from 10 volunteers concluded that any presented character was identified correctly in 7 out 10 tests. The second test included characters that were reused from the first experiment. Users had improved their character recognition performance as a consequence of repeated exposure and learning. A final set of experiments concluded that recognition of groups of characters, forming words, is the least efficient and requires further perfecting. Recommendations for improvements of the recognition rate are also included.

scholarly journals Raspberry Pi based Object Detection and Text Reader using Voice Assistance

2021 ◽  
Vol 9 (VIII) ◽  
pp. 157-160
Author(s):  
Sushmitha M
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Experimental Result ◽  
Raspberry Pi ◽  
Visually Impaired People ◽  
Impaired People ◽  
Scanned Image ◽  
Recognition Software ◽  
Processor Board

Communication is the basic requirement for humans to connect and it requires text and speech but visually impaired people cannot able to perform this. This project helps them to read the image. This project is an automatic document reader for visually impaired people, developed on the Raspberry Pi processor board. It controls the peripherals like a camera, a speaker which acts as an interface between the system and the user. Here, we use a raspberry pi camera which is used to capture the image and scan the image using Image Magick software. Then the output of the scanned image is given to OCR(optical character recognition) software to convert the image to text. It converts the typed or printed text to the machine code. Then we use Text to Speech (TTS), which is used to convert speech to text. The experimental result is very helpful to blind people as there was much analysis of the different objects.

Automated Text Detection and Recognition in Annotated Biomedical Publication Images

2014 ◽  
Vol 9 (2) ◽  
pp. 34-63 ◽  
Author(s):  
Soumya De ◽  
R. Joe Stanley ◽  
Beibei Cheng ◽  
Sameer Antani ◽  
Rodney Long ◽  
...  
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Recognition Rate ◽  
Regions Of Interest ◽  
Correct Recognition ◽  
Support Vector ◽  
Data Set ◽  
Biomedical Publication ◽  
Biomedical Publications ◽  
Detection And Recognition

Images in biomedical publications often convey important information related to an article's content. When referenced properly, these images aid in clinical decision support. Annotations such as text labels and symbols, as provided by medical experts, are used to highlight regions of interest within the images. These annotations, if extracted automatically, could be used in conjunction with either the image caption text or the image citations (mentions) in the articles to improve biomedical information retrieval. In the current study, automatic detection and recognition of text labels in biomedical publication images was investigated. This paper presents both image analysis and feature-based approaches to extract and recognize specific regions of interest (text labels) within images in biomedical publications. Experiments were performed on 6515 characters extracted from text labels present in 200 biomedical publication images. These images are part of the data set from ImageCLEF 2010. Automated character recognition experiments were conducted using geometry-, region-, exemplar-, and profile-based correlation features and Fourier descriptors extracted from the characters. Correct recognition as high as 92.67% was obtained with a support vector machine classifier, compared to a 75.90% correct recognition rate with a benchmark Optical Character Recognition technique.

scholarly journals A Deep Learning Technology based OCR Framework for Recognition Handwritten Expression and Text

CONVERTER ◽  
2021 ◽  
pp. 01-10
Author(s):  
Tuanji Gong, Xuanxia Yao
Keyword(s):  
Deep Learning ◽  
Online Education ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Mathematical Expression ◽  
Text Recognition ◽  
Learning Technology ◽  
Expression Recognition ◽  
Features Selection ◽  
Handwritten Text Recognition

Recently Optical character recognition (OCR) based on deep learning technology has achieved great advance and broadly applied in various industries. However it still faces many challenging problems in handwritten text recognition and mathematical expression recognition, such as handwritten Chinese recognition, mixture of printed and handwritten Chinese characters, mathematical expression (ME), chemical equations. In traditional OCR, features selection played a vital role for recognition accuracy, while hand-crafted features are costly and time-consuming. In this paper, we introduce a deep learning based framework to detect and recognize handwritten and printed text or math expression. The framework consists of three components. The first component is DCN (Detection & Classification Network), which based on SSD model to detects and classify mathematical expression and text. The second component consists of text recognition and ME recognition models. The final component merges multiple outputs of the second stage into a whole text. Experiment results show that our framework achieves a relative 10% improvement in mixture of texts and MEs which are printed or handwritten in images. The framework has been deployed for recognition paper or homework at one online education platform.

scholarly journals VirtualEye: Android Application for the Visually Impaired

2021 ◽  
Author(s):  
Jay Bagrecha ◽  
Tanay Shah ◽  
Karan Shah ◽  
Tanvi Gandhi ◽  
Sushila Palwe
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Android Application ◽  
Visually Impaired People ◽  
Currency Note ◽  
Visually Challenged ◽  
Blind User ◽  
User Friendly

In India, almost 18 million visually impaired people have difficulties in managing their day-to-day activities. Hence, there is a need to develop an application that can assist them every time and give vocal instructions in both English and Hindi. In this paper, we introduced a robust lightweight Android application that facilitates visually impaired individuals by providing a variety of essential features such as object and distance detection, Indian currency note detection, and optical character recognition that can enhance their quality of life. This application aims to have a user-friendly GUI well suited to the needs of the blind user and modules like Object Recognition with Image Captioning so that the visually challenged user can gain a better understanding of their surroundings.

scholarly journals Intelligent Assistive System for Visually Disabled Persons

2019 ◽  
Vol 8 (4) ◽  
pp. 1436-1440
Keyword(s):  
Optical Character Recognition ◽  
Visually Impaired ◽  
Disabled Persons ◽  
Obstacle Detection ◽  
Outdoor Environment ◽  
Assistive Device ◽  
Raspberry Pi ◽  
New Device ◽  
Visually Impaired People ◽  
Impaired People

There is increasin demand for smart widgets which make people more comfortable. Though many research works have done on current existing devices/systems for visually impaired people are not providing facilities them enough. The imperceptible people read Braille scripted books only, so here developing a new device that will assist the visually impaired people and also providing desired language reading facility. This smart assistive device will help visually impaired people gain increased independence and freedom in society. This device has an obstacle detection sensor to intimate the obstacles to the visually impaired person and a camera connected to Raspberry pi to convert image to text using Optical Character Recognition (OCR). The read data is converted to speech using text to speech synthesizer. This will useful for visually impaired people for surviving in outdoor environment as well as reading books which are in normal script. The read data can be stored in database for further reading and it can be retrieve by giving a command.

scholarly journals A Smart Reader for Blind People

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1566-1568
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Raspberry Pi ◽  
Human Communication ◽  
Human Needs ◽  
Normal People ◽  
Optical Character ◽  
Visually Impaired People ◽  
Visually Challenged

This paper presents an intelligent bot for aiding the visually challenged people. Presently, 81% are visually impaired who live in the developing countries. Nowadays Human communication is mainly focused on text and speech. To read the text a human needs a vision. Survey conducted on several papers and systems provides hardware consisting of a camera interface with Raspberry Pi for processing the text. The camera captures text image of a handwritten or printed text. The raspberry pi makes use of Optical Character Recognition (OCR) software installed in it, to perform the conversion of an image to text and similarly text to speech conversion. The assistant is applicable for visually impaired people as well as for normal people in order to increase their level of comfort.

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