scholarly journals A Comparative Review on Object Detection System for Visually Impaired

2021 ◽  
Vol 12 (2) ◽  
pp. 1598-1610
Author(s):  
Dr K Sreenivasulu, Et. al.
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Detection System ◽  
Voice Quality ◽  
Natural World ◽  
Blind People ◽  
Visual Disability ◽  
Comparative Review ◽  
Audio Output ◽  
The Voice

Vision is one of the key senses allowing citizens to communicate with the natural world. There are about two hundred million blind people globally and visually disabled people obstruct numerous everyday practices. It is also really critical that blind people recognize their world and realize with which items they communicate. This paper review all the method and tool related to camera-based device to enable the blind person interpret text patterns written on items kept in hand.  This is the system for helping individuals with visual disability interpret and translate text patterns to the audio output. The framework first suggests the approach to take an image from the camera and the area of the target to retrieve the object from the context and derive a text pattern from that object. Diffrent algorithm is assessed in various scenes. The observed text is linked to the blueprint and translated into the performance of the voice. Localized and binarized text patterns utilising Optical Character Recognition (OCR). The text is translated to an audio output. The voice quality is given to theblind person.  

scholarly journals Transcript Anatomization with Multi-Linguistic and Speech Synthesis Features

2021 ◽  
Vol 9 (VI) ◽  
pp. 1755-1758
Author(s):  
Rohan Modi
Keyword(s):  
Pattern Recognition ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Speech Synthesis ◽  
Handwriting Recognition ◽  
Cost Effective ◽  
Computer Hardware ◽  
Handwritten Text ◽  
Handwritten Text Recognition ◽  
Audio Output

Handwriting Detection is a process or potential of a computer program to collect and analyze comprehensible input that is written by hand from various types of media such as photographs, newspapers, paper reports etc. Handwritten Text Recognition is a sub-discipline of Pattern Recognition. Pattern Recognition is refers to the classification of datasets or objects into various categories or classes. Handwriting Recognition is the process of transforming a handwritten text in a specific language into its digitally expressible script represented by a set of icons known as letters or characters. Speech synthesis is the artificial production of human speech using Machine Learning based software and audio output based computer hardware. While there are many systems which convert normal language text in to speech, the aim of this paper is to study Optical Character Recognition with speech synthesis technology and to develop a cost effective user friendly image based offline text to speech conversion system using CRNN neural networks model and Hidden Markov Model. The automated interpretation of text that has been written by hand can be very useful in various instances where processing of great amounts of handwritten data is required, such as signature verification, analysis of various types of documents and recognition of amounts written on bank cheques by hand.

scholarly journals IMPLEMENTASI ALGORITMA YOLO DAN TESSERACT OCR PADA SISTEM DETEKSI PLAT NOMOR OTOMATIS

2022 ◽  
Vol 16 (1) ◽  
pp. 54
Author(s):  
Imam Husni Al amin ◽  
Awan Aprilino
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Detection System ◽  
Extraction Process ◽  
Test Results ◽  
Web Based ◽  
Detection Systems ◽  
Human Labor ◽  
Cross Platform ◽  
Human Effort

Currently, vehicle number plate detection systems in general still use the manual method. This will take a lot of time and human effort. Thus, an automatic vehicle number plate detection system is needed because the number of vehicles that continues to increase will burden human labor. In addition, the methods used for vehicle number plate detection still have low accuracy because they depend on the characteristics of the object being used. This study develops a YOLO-based automatic vehicle number plate detection system. The dataset used is a pretrained YOLOv3 model of 700 data. Then proceed with the number plate text extraction process using the Tesseract Optical Character Recognition (OCR) library and the results obtained will be stored in the database. This system is web-based and API so that it can be used online and on the cross-platform. The test results show that the automatic number plate detection system reaches 100% accuracy with sufficient lighting and a threshold of 0.5 and for the results using the Tesseract library, the detection results are 92.32% where the system is successful in recognizing all characters on the license plates of cars and motorcycles. in the form of Alphanumeric characters of 7-8 characters.

Real Time Implementation of Optical Character Recognition Based TTS System using Raspberry pi

2017 ◽  
Vol 7 (7) ◽  
pp. 149
Author(s):  
Sagar G. K ◽  
Shreekanth T
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
World Health ◽  
Raspberry Pi ◽  
Blind People ◽  
Poor Vision ◽  
Input Text ◽  
Optical Character ◽  
Health Organization ◽  
Text Page

Thetext to speech (TTS) conversion technology is proposed to help the blind people and people with poor vision. According to survey done by World Health Organization (WHO) there are about 286 million blind people in this world and about 91% of them reside in developing countries. So there is necessity of portable TTS converter which should be affordable to help the blinds. To help the blind community a smart reader is proposed in this paper. It includes a web cam to capture input text page which is then processed by TTS unit installed in raspberry pi and the output is then amplified by audio and given out on speaker.

scholarly journals Smart Glass for Visually Challenged Peoples to Read the Books using Raspberry Pi

2021 ◽  
pp. 258-262
Author(s):  
Anitha D B ◽  
Jyothi T M ◽  
Pooja R ◽  
Sahana N
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Computer Software ◽  
Raspberry Pi ◽  
Text To Speech ◽  
Smart Glasses ◽  
Optical Character ◽  
Text Reading ◽  
Visually Challenged ◽  
Audio Output

The objective of this paper is to presents new design on assistive smart glasses for visually impaired. The objective is to assist in multiple daily tasks using the advantage of wearable design format. The proposed method is a camera based assistive text reading to help to blind in person in reading the text present on the text labels, printed notes and products in their own respective languages. It combines the concept of Optical Character Recognition (OCR), text to Speech Synthesizer (TTS) and translator in Raspberry pi. Optical character recognition (OCR) is the identification of printed characters using photoelectric devices and computer software. It converts images of typed, handwritten or printed text into machine encoded text from scanned document or from subtitle text superimposed on an image. Text-to-Speech conversion is a method that scans and reads any language letters and numbers that are in the image using OCR technique and then translates it into any desired language and at last it gives audio output of the translated text. The audio output is heard through the raspberry pi's audio jack using speakers or earphones.

scholarly journals Detection of Non-Helmet Riders and Extraction of License Plate Number using Yolo v2 and OCR Method

2019 ◽  
Vol 9 (2) ◽  
pp. 5167-5172
Keyword(s):  
Object Detection ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Detection System ◽  
Research Work ◽  
License Plate ◽  
Plate Number ◽  
Traffic Violations ◽  
Registration Number ◽  
Traffic Violation

In current situation, we come across various problems in traffic regulations in India which can be solved with different ideas. Riding motorcycle/mopeds without wearing helmet is a traffic violation which has resulted in increase in number of accidents and deaths in India. Existing system monitors the traffic violations primarily through CCTV recordings, where the traffic police have to look into the frame where the traffic violation is happening, zoom into the license plate in case rider is not wearing helmet. But this requires lot of manpower and time as the traffic violations frequently and the number of people using motorcycles is increasing day-by-day. What if there is a system, which would automatically look for traffic violation of not wearing helmet while riding motorcycle/moped and if so, would automatically extract the vehicles’ license plate number. Recent research have successfully done this work based on CNN, R-CNN, LBP, HoG, HaaR features,etc. But these works are limited with respect to efficiency, accuracy or the speed with which object detection and classification is done. In this research work, a Non-Helmet Rider detection system is built which attempts to satisfy the automation of detecting the traffic violation of not wearing helmet and extracting the vehicles’ license plate number. The main principle involved is Object Detection using Deep Learning at three levels. The objects detected are person, motorcycle/moped at first level using YOLOv2, helmet at second level using YOLOv3, License plate at the last level using YOLOv2. Then the license plate registration number is extracted using OCR (Optical Character Recognition). All these techniques are subjected to predefined conditions and constraints, especially the license plate number extraction part. Since, this work takes video as its input, the speed of execution is crucial. We have used above said methodologies to build a holistic system for both helmet detection and license plate number extraction.

scholarly journals Prototype to Help Visually Impaired Person in Reading Printed Learning Materials using Raspberry PI

2018 ◽  
Vol 7 (3.1) ◽  
pp. 82
Author(s):  
Jaichandran R ◽  
Somasundaram K ◽  
Bhagyashree Basfore ◽  
Menaka I.S ◽  
Uma S
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
Visually Impaired ◽  
Raspberry Pi ◽  
Learning Materials ◽  
Line Spacing ◽  
Impaired Person ◽  
Audio Output ◽  
Visually Impaired Persons

This paper presents a prototype to help visually impaired persons in reading printed learning materials using Raspberry PI. Tesseract an open source optical character recognition technique is used extract texts in printed images and converted to audio output using text-to-speech conversion software. Prototype is experimented using printed text pages with various font sizes and line spacing as test cases. Results show that the prototype is better in converting printed texts to speech. However quality of image, font size, and line space affects performance of prototype in converting printed texts to speech.. 

scholarly journals An Illegal Dumping Detection System Based on Image Processing in OpenALPR

2021 ◽  
Vol 15 ◽  
pp. 1-7
Author(s):  
Wan Zakiah Wan Ismail
Keyword(s):  
Real Time ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Detection System ◽  
Social Economy ◽  
Raspberry Pi ◽  
License Plate ◽  
Microwave Radar ◽  
Plate Number ◽  
Illegal Dumping

Tipping or depositing large waste onto land using unauthorized and unlicensed methods are considered as illegal dumping. The increasing rate of illegal dumping becomes a crucial nation issue because this activity causes negative impacts to social, economy and environment. Thus, study on detecting the dumping activities is conducted to control the illegal dumping activities in Malaysia. Raspberry Pi with Python language is used as the microprocessor and a Raspberry Pi camera module with a microwave radar sensor are interfaced to it to capture the image of any vehicles entering the illegal dumping site. The image is captured to recognize the license plate of the vehicle. The method in this study is by using Open Automatic License Plate Recognition (ALPR), Open Computer Vision (CV) libraries and Optical Character Recognition (OCR) to detect the character of the plate registration number. The outcome of the study consists of recognition of Malaysia vehicles’ plate number and the automatic real time email notification on the illegal dumping case. The detection system can be used for case monitoring since the plate number recognition is done in real time. The system can be upgraded to ensure its sustainability in the harsh and isolated environment.

The contribution of technologies to the inclusion of the student whit a visual disability: the "smart stick for blind people"

2018 ◽  
Author(s):  
Michele Aurelio ◽  
Stefania Cecchi ◽  
Mirca Montanari ◽  
Andrea Primavera
Keyword(s):  
Collaborative Teaching ◽  
Training Needs ◽  
Blind People ◽  
Visual Disability ◽  
Innovative Teaching ◽  
Digital Education ◽  
Design And Construction

Taking into consideration the complexity of the new, heterogeneous, and different training needs currently present in the classrooms, the school is called to respond them in an effective and concrete way through inclusive educational approaches centered on the students, none excluded. On this basis, the authors, supporting the importance of technology in innovative teaching, propose the design and construction of an intelligent white stick through an inclusive cooperative methodology. The presented device, presented in this paper, is inspired by an open and collaborative teaching, enhancing a responsible digital education, accepting the training needs of all the students present in the classroom, specifically the blind student, and the recognition of the diversity in view of the reduction of disability.

Petunjuk Waktu Untuk Tuna Netra Dengan Output Suara

2019 ◽  
Vol 10 (02) ◽  
pp. 1-7
Author(s):  
Aan Febriansyah ◽  
Muslim Fathillah ◽  
Nurdin Nurdin
Keyword(s):  
Special Needs ◽  
Blind People ◽  
Storage Unit ◽  
Level Indicator ◽  
Normal People ◽  
The Voice ◽  
Time Information ◽  
Voice Output

Nowaday time indicator as hour and calendar constitutes necessary for thing a lot of person to trip routines. In general, the clock and the calendar can only be seen by normal people. People with special needs, its example is blind will have difficulty in using the clock and the calendar Get bearing with that problem, therefore to help that blind is designed and made by time indicator tool with voice output. Generally, the tool's instructions when using RTC DS1307, is microcontroller ATmega16 and ISD 25 120. Information about hour, minute, date, month, and year obtained from DS1307 RTC is accessed using microcontroller ATmega16, then from the data when the information obtained is matched in the voice storage unit on ISD25120. As a results,will be obtained time information data such as voice. Besides, time setting, alarm, battery level indicator, and charge the battery with the sound as well is the tool is equipped permanently. Finally, this tool can help the blind people to be more independent in making it easier to tell the time in living day-to-day activities.

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