A Dual-Purpose Refreshable Braille Display Based on Real Time Object Detection and Optical Character Recognition

2019 ◽  
Author(s):  
K M Naimul Hassan ◽  
Subrata Kumar Biswas ◽  
Md Shakil Anwar ◽  
Md Shakhrul Iman Siam ◽  
Celia Shahnaz
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Dual Purpose ◽  
Optical Character ◽  
Braille Display

ConvNet-Based Optical Recognition for Engineering Drawings

2017 ◽  
Author(s):  
Andrew Brock ◽  
Theodore Lim ◽  
J. M. Ritchie ◽  
Nick Weston
Keyword(s):  
Object Detection ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Cross Validation ◽  
Convolutional Networks ◽  
Optical Character ◽  
Engineering Drawings ◽  
Machine Analysis ◽  
Fold Cross Validation ◽  
Optical Recognition

End-to-end machine analysis of engineering document drawings requires a reliable and precise vision frontend capable of localizing and classifying various characters in context. We develop an object detection framework, based on convolutional networks, designed specifically for optical character recognition in engineering drawings. Our approach enables classification and localization on a 10-fold cross-validation of an internal dataset for which other techniques prove unsuitable.

scholarly journals Computer Vision for Continuous Bedside Pharmacological Data Extraction: A Novel Application of Artificial Intelligence for Clinical Data Recording and Biomedical Research

2021 ◽  
Vol 4 ◽  
Author(s):  
Logan Froese ◽  
Joshua Dian ◽  
Carleen Batson ◽  
Alwyn Gomez ◽  
Amanjyot Singh Sainbhi ◽  
...  
Keyword(s):  
Computer Vision ◽  
Data Integration ◽  
Real Time ◽  
Clinical Data ◽  
Biomedical Research ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Time Data ◽  
Optical Character ◽  
Real Time Data

Introduction: As real time data processing is integrated with medical care for traumatic brain injury (TBI) patients, there is a requirement for devices to have digital output. However, there are still many devices that fail to have the required hardware to export real time data into an acceptable digital format or in a continuously updating manner. This is particularly the case for many intravenous pumps and older technological systems. Such accurate and digital real time data integration within TBI care and other fields is critical as we move towards digitizing healthcare information and integrating clinical data streams to improve bedside care. We propose to address this gap in technology by building a system that employs Optical Character Recognition through computer vision, using real time images from a pump monitor to extract the desired real time information.Methods: Using freely available software and readily available technology, we built a script that extracts real time images from a medication pump and then processes them using Optical Character Recognition to create digital text from the image. This text was then transferred to an ICM + real-time monitoring software in parallel with other retrieved physiological data.Results: The prototype that was built works effectively for our device, with source code openly available to interested end-users. However, future work is required for a more universal application of such a system.Conclusion: Advances here can improve medical information collection in the clinical environment, eliminating human error with bedside charting, and aid in data integration for biomedical research where many complex data sets can be seamlessly integrated digitally. Our design demonstrates a simple adaptation of current technology to help with this integration.

scholarly journals Tanslator Real-Time Bahasa Indonesia - Tombulu dan Tombulu - Indonesia menggunakan Augmented Reality

2016 ◽  
Vol 2 (2) ◽  
pp. 194
Author(s):  
Andria Wahyudi ◽  
Andre Sumual ◽  
Jorgie Sumual
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Optical Character ◽  
Bahasa Indonesia

Penelitian ini membahas tentang gabungan beberapa teknologi untuk perancangan aplikasi translasi bahasa menggunakan teknologi Augmented Reality (AR) pada smartphone dengan sistem operasi Android. Tujuan utama dari penelitian ini adalah penerapan AR pada media translasi bahasa Tombulu dan Indonesia menggunakan SDK Vuforia. Vuforia digunakan untuk menampilkan teks secara real-time, dimana teknologi Optical Character Recognition (OCR) sudah menjadi fitur didalamnya yang digunakan  untuk melakukan pendeteksian teks. Setelah aplikasi selesai dibuat, dilakukan pengujian kemampuan deteksi dari aplikasi. Pengujian tersebut dimulai dari deteksi tulisan tangan, teks berwarna, typeface yang berbeda, typeface yang mengandung symbol, dan kata yang mengandung spasi. Adapun pengujian dengan cara manual, yaitu dengan mengetikan sendiri teks ke smartphone. Hasil yang di dapatkan adalah batas kemampuan maksimum dalam melakukan pendeteksian teks sesuai pengujian yang telah ditentukan sebelumya.Kata Kunci: Augmented Reality, Translation, Vuforia SDK, OCR

scholarly journals A Real-Time Automatic Plate Recognition System Based on Optical Character Recognition and Wireless Sensor Networks for ITS

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 55
Author(s):  
Nicole do Vale Dalarmelina ◽  
Marcio Andrey Teixeira ◽  
Rodolfo I. Meneguette
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Recognition System ◽  
Transportation Systems ◽  
Identification System ◽  
License Plate ◽  
Optical Character ◽  
Smart Parking

Automatic License Plate Recognition has been a recurrent research topic due to the increasing number of cameras available in cities, where most of them, if not all, are connected to the Internet. The video traffic generated by the cameras can be analyzed to provide useful insights for the transportation segment. This paper presents the development of an intelligent vehicle identification system based on optical character recognition (OCR) method to be used on intelligent transportation systems. The proposed system makes use of an intelligent parking system named Smart Parking Service (SPANS), which is used to manage public or private spaces. Using computer vision techniques, the SPANS system is used to detect if the parking slots are available or not. The proposed system makes use of SPANS framework to capture images of the parking spaces and identifies the license plate number of the vehicles that are moving around the parking as well as parked in the parking slots. The recognition of the license plate is made in real-time, and the performance of the proposed system is evaluated in real-time.

YOLOv3-Tesseract model for improved intelligent form recognition

2019 ◽  
Vol 13 ◽  
Author(s):  
Zhang Yun-An ◽  
Pan Ziheng ◽  
Dui Hongyan ◽  
Bai Guanghan
Keyword(s):  
Big Data ◽  
Object Detection ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Recognition Task ◽  
Experimental Simulation ◽  
Form Recognition ◽  
Optical Character

Background: YOLOv3-Tesseract is widely used for the intelligent form recognition because it exhibits several attractive properties. It is important to improve the accuracy and efficiency of the optical character recognition. Methods: The YOLOv3 exhibits the classification advantages for the object detection. Tesseract can effectively recognize regular characters in the field of the optical character recognition. In this study, a YOLOv3 and Tesseract-based model of improved intelligent form recognition is proposed. Results: First, YOLOv3 is trained to detect the position of the text in the table and to subsequently segment text blocks. Second, Tesseract is used to individually detect separated text blocks and combine YOLOv3 and Tesseract to achieve the goal of table character recognition. Conclusion: Based on the Tianchi big data, experimental simulation is used to demonstrate the proposed method. The YOLOv3-Tesseract model is trained and tested to effectively accomplish the recognition task.

Finger Spelling in Air System for Deaf and Dumb

2018 ◽  
Vol 9 (1) ◽  
pp. 28-44
Author(s):  
Urmila Shrawankar ◽  
Shruti Gedam
Keyword(s):  
Real Time ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Human Interaction ◽  
Finger Movements ◽  
Accuracy Rate ◽  
Optical Character ◽  
Average Accuracy ◽  
Bright Color ◽  
Natural Way

Finger spelling in air helps user to operate a computer in order to make human interaction easier and faster than keyboard and touch screen. This article presents a real-time video based system which recognizes the English alphabets and words written in air using finger movements only. Optical Character Recognition (OCR) is used for recognition which is trained using more than 500 various shapes and styles of all alphabets. This system works with different light situations and adapts automatically to various changing conditions; and gives a natural way of communicating where no extra hardware is used other than system camera and a bright color tape. Also, this system does not restrict writing speed and color of tape. Overall, this system achieves an average accuracy rate of character recognition for all alphabets of 94.074%. It is concluded that this system is very useful for communication with deaf and dumb people.

Sign in / Sign up

Export Citation Format

Share Document