№ files_lp_4_process_2_69128
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Academic research paper describing an OCR-based assistive vision system that converts captured images of printed or handwritten text into speech output using Raspberry Pi hardware and Tesseract text recognition algorithms for visually impaired users.
Authors: Praveena S., Sowmiya N., Thenmozhi M., Manoharan L.
Institution: Jeppiaar SRR Engineering College
Department: Department of Electronics and Communication Engineering
Author roles: UG Student; Assistant Professor
Academic field: Electronics and Communication Engineering
Topic: Optical Character Recognition and assistive technology for visually impaired users
Technologies mentioned: Raspberry Pi 3; Tesseract algorithm; Python; HDMI to VGA converter; Ultrasonic sensor
Keywords: OCR Technology; Raspberry Pi3; HDMI to VGA converter; Tesseract algorithm
Document type: Academic research paper
Research area: Computer vision; Artificial Intelligence; Digital Image Analysis
Application domain: Assistive reading system for blind and visually impaired people
Input data: Images of printed or handwritten text captured by camera
Output format: Speech audio generated from recognized text
Recognition method: Text localization with gradient features and Adaboost model followed by Tesseract OCR recognition
Algorithm features: Motion-based object detection and region-of-interest localization
Reported performance: Approximately 90% success rate on the test set
Hardware platform: Raspberry Pi device with camera and sensors
Price: 8 / 10 USD
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TP DécouverteCarte RASPBERRY PI
Année: 2012
Région / ville: Cambridge
Thématique: Programmation et architecture informatique
Type de document: Fiche technique
Organisme / établissement: Fondation Raspberry Pi
Auteur: Eben Upton
Public cible: Étudiants en informatique, amateurs de programmation
Date de modification: Aucune mention
Analysis of the ionospheric source of geomagnetic Pi3 pulsations on September 4, 2022
Year: 2022
Region / City: Global observations, data from Canada, Russia
Subject: Geomagnetic Pi3 pulsations
Document Type: Research article
Institutions: Polar Geophysical Institute, Institute of Solar-Terrestrial Physics of the Siberian Branch of the RAS, Institute of Physics of the Earth
Authors: Belakhovsky V.B., Pilipenko V.A.
Data Sources: CARISMA and THEMIS magnetometer networks, NORSTAR riometers, GOES, MMS, THEMIS, and Cluster satellites
Event Type: Moderate-intensity magnetic storm (Dst = -71 nT) with substorms (~1500 nT)
Observation Date: September 4, 2022
Funding: Russian Science Foundation, grant № 24-77-10012
Analysis Focus: Ionospheric contribution to geomagnetic Pi3 pulsations and their interaction with magnetospheric waves
Document Scope: Space physics and geomagnetic storm phenomena
Research Method: Satellite and ground-based measurements, data detrending and smoothing, comparison of conjugated stations and satellites
Topics: Vision-Impaired Raspberry Pi3