An Accuracy Examination of OCR Tools
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OCR Pwds and Assistive Qatari Using OCR Issue No
Arabic Optical State of the Smart Character Art in Arabic Apps for Recognition OCR PWDs and Assistive Qatari using OCR Issue no. 15 Technology Research Nafath Efforts Page 04 Page 07 Page 27 Machine Learning, Deep Learning and OCR Revitalizing Technology Arabic Optical Character Recognition (OCR) Technology at Qatar National Library Overview of Arabic OCR and Related Applications www.mada.org.qa Nafath About AboutIssue 15 Content Mada Nafath3 Page Nafath aims to be a key information 04 Arabic Optical Character resource for disseminating the facts about Recognition and Assistive Mada Center is a private institution for public benefit, which latest trends and innovation in the field of Technology was founded in 2010 as an initiative that aims at promoting ICT Accessibility. It is published in English digital inclusion and building a technology-based community and Arabic languages on a quarterly basis 07 State of the Art in Arabic OCR that meets the needs of persons with functional limitations and intends to be a window of information Qatari Research Efforts (PFLs) – persons with disabilities (PWDs) and the elderly in to the world, highlighting the pioneering Qatar. Mada today is the world’s Center of Excellence in digital work done in our field to meet the growing access in Arabic. Overview of Arabic demands of ICT Accessibility and Assistive 11 OCR and Related Through strategic partnerships, the center works to Technology products and services in Qatar Applications enable the education, culture and community sectors and the Arab region. through ICT to achieve an inclusive community and educational system. The Center achieves its goals 14 Examples of Optical by building partners’ capabilities and supporting the Character Recognition Tools development and accreditation of digital platforms in accordance with international standards of digital access. -
Reconocimiento De Escritura Lecture 4/5 --- Layout Analysis
Reconocimiento de Escritura Lecture 4/5 | Layout Analysis Daniel Keysers Jan/Feb-2008 Keysers: RES-08 1 Jan/Feb-2008 Outline Detection of Geometric Primitives The Hough-Transform RAST Document Layout Analysis Introduction Algorithms for Layout Analysis A `New' Algorithm: Whitespace Cuts Evaluation of Layout Analyis Statistical Layout Analysis OCR OCR - Introduction OCR fonts Tesseract Sources of OCR Errors Keysers: RES-08 2 Jan/Feb-2008 Outline Detection of Geometric Primitives The Hough-Transform RAST Document Layout Analysis Introduction Algorithms for Layout Analysis A `New' Algorithm: Whitespace Cuts Evaluation of Layout Analyis Statistical Layout Analysis OCR OCR - Introduction OCR fonts Tesseract Sources of OCR Errors Keysers: RES-08 3 Jan/Feb-2008 Detection of Geometric Primitives some geometric entities important for DIA: I text lines I whitespace rectangles (background in documents) Keysers: RES-08 4 Jan/Feb-2008 Outline Detection of Geometric Primitives The Hough-Transform RAST Document Layout Analysis Introduction Algorithms for Layout Analysis A `New' Algorithm: Whitespace Cuts Evaluation of Layout Analyis Statistical Layout Analysis OCR OCR - Introduction OCR fonts Tesseract Sources of OCR Errors Keysers: RES-08 5 Jan/Feb-2008 Hough-Transform for Line Detection Assume we are given a set of points (xn; yn) in the image plane. For all points on a line we must have yn = a0 + a1xn If we want to determine the line, each point implies a constraint yn 1 a1 = − a0 xn xn Keysers: RES-08 6 Jan/Feb-2008 Hough-Transform for Line Detection The space spanned by the model parameters a0 and a1 is called model space, parameter space, or Hough space. -
Master Thesis
Master thesis To obtain a Master of Science Degree in Informatics and Communication Systems from the Merseburg University of Applied Sciences Subject: Tunisian truck license plate recognition using an Android Application based on Machine Learning as a detection tool Author: Supervisor: Achraf Boussaada Prof.Dr.-Ing. Rüdiger Klein Matr.-Nr.: 23542 Prof.Dr. Uwe Schröter Table of contents Chapter 1: Introduction ................................................................................................................................. 1 1.1 General Introduction: ................................................................................................................................... 1 1.2 Problem formulation: ................................................................................................................................... 1 1.3 Objective of Study: ........................................................................................................................................ 4 Chapter 2: Analysis ........................................................................................................................................ 4 2.1 Methodological approaches: ........................................................................................................................ 4 2.1.1 Actual approach: ................................................................................................................................... 4 2.1.2 Image Processing with OCR: ................................................................................................................ -
Enforcing Abstract Immutability
Enforcing Abstract Immutability by Jonathan Eyolfson A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Doctor of Philosophy in Electrical and Computer Engineering Waterloo, Ontario, Canada, 2018 © Jonathan Eyolfson 2018 Examining Committee Membership The following served on the Examining Committee for this thesis. The decision of the Examining Committee is by majority vote. External Examiner Ana Milanova Associate Professor Rensselaer Polytechnic Institute Supervisor Patrick Lam Associate Professor University of Waterloo Internal Member Lin Tan Associate Professor University of Waterloo Internal Member Werner Dietl Assistant Professor University of Waterloo Internal-external Member Gregor Richards Assistant Professor University of Waterloo ii I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. iii Abstract Researchers have recently proposed a number of systems for expressing, verifying, and inferring immutability declarations. These systems are often rigid, and do not support “abstract immutability”. An abstractly immutable object is an object o which is immutable from the point of view of any external methods. The C++ programming language is not rigid—it allows developers to express intent by adding immutability declarations to methods. Abstract immutability allows for performance improvements such as caching, even in the presence of writes to object fields. This dissertation presents a system to enforce abstract immutability. First, we explore abstract immutability in real-world systems. We found that developers often incorrectly use abstract immutability, perhaps because no programming language helps developers correctly implement abstract immutability. -
CSI: Inferring Mobile ABR Video Adaptation Behavior Under HTTPS and QUIC
CSI: Inferring Mobile ABR Video Adaptation Behavior under HTTPS and QUIC Shichang Xu Subhabrata Sen Z. Morley Mao University of Michigan AT&T Labs – Research University of Michigan Abstract Server Manifest Network Client Mobile video streaming services have widely adopted Adap- Chunks HTTP tive Bitrate (ABR) streaming to dynamically adapt the stream- Track ing quality to variable network conditions. A wide range of 720p 1 Buffer third-party entities such as network providers and testing 480p IP packets services need to understand such adaptation behavior for 360p 1 2 3 Index purposes such as QoE monitoring and network management. CSI The traditional approach involved conducting test runs and analyzing the HTTP-level information from the associated network traffic to understand the adaptation behavior under Figure 1. ABR streaming overview different network conditions. However, end-to-end traffic encryption protocols such as HTTPS and QUIC are being increasingly used by streaming services, hindering such tra- Rate (ABR) streaming (predominantly HLS [75] and DASH [31]) ditional traffic analysis approaches. has been widely adopted in industry for delivering satisfac- To address this, we develop CSI (Chunk Sequence Infer- tory Quality of Experience (QoE) over dynamic cellular net- encer), a general system that enables third-parties to conduct work conditions. The server encodes each video into multiple active measurements and infer mobile ABR video adapta- versions with different picture quality levels and encoding tion behavior based on packet size and timing information bitrates (with higher bitrates for higher-quality encodings) still available in the encrypted traffic. We perform exten- called tracks, and splits each track into shorter chunks, each sive evaluations and demonstrate that CSI achieves high representing a few seconds worth of playback content (Fig- inference accuracy for video encodings of popular streaming ure 1). -
Expense Tracking Mobile Application with Receipt Scanning Functionality Bachelor’S Thesis
TALLINN UNIVERSITY OF TECHNOLOGY Faculty of Information Technology Department of Computer Science Chair of Network Software Expense tracking mobile application with receipt scanning functionality Bachelor’s thesis Student: Roman Kaskman Student code: 113089 IAPB Advisor: Roger Kerse Tallinn 2015 Author’s declaration I declare that this thesis is the result of my own research except as cited in the references. The thesis has not been accepted for any degree and is not concurrently submitted in candidature of any other degree. 25.05.2015 Roman Kaskman (date) (signature) Abstract The purpose of this thesis is to create a mobile application for expense tracking, with the main focus on functionality allowing to take pictures of receipts issued by Estonian enterprises, extract basic expense information from the captured receipt images and store extracted expenses information in authenticated user’s expense list. The main problems covered in this work are finding the best architectural and design solutions for the application from the perspective of performance, usability, security and further development as well as researching and implementing techniques to handle expense recognition from receipts in an efficient way. As a result of the thesis, a working implementation of expense tracking mobile application for Android appears. After functionality of expenses information extraction from receipt images passes the testing phase, conclusion regarding its reliability is made. Moreover, proposals for further improvements of the application’s functionality are also presented. The thesis is in English and contains 53 pages of text, 6 chapters and 14 figures. Annotatsioon Käesoleva bakalaureusetöö eesmärk on luua mobiilirakendus kasutaja kulude üle arvestuse pidamiseks ja dokumenteerimiseks. -
Character Recognition in Natural Images Utilising Tensorflow
DEGREE PROJECT IN TECHNOLOGY, FIRST CYCLE, 15 CREDITS STOCKHOLM, SWEDEN 2017 Character Recognition in Natural Images Utilising TensorFlow ALEXANDER VIKLUND EMMA NIMSTAD KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF COMPUTER SCIENCE AND COMMUNICATION Character Recognition in Natural Images Utilising TensorFlow ALEXANDER VIKLUND EMMA NIMSTAD Degree project in Computer Science, DD143X Date: June 12, 2017 Supervisor: Kevin Smith Examiner: Örjan Ekeberg Swedish title: Teckenigenkänning i naturliga bilder med TensorFlow School of Computer Science and Communication Abstract Convolutional Neural Networks (CNNs) are commonly used for character recogni- tion. They achieve the lowest error rates for popular datasets such as SVHN and MNIST. Usage of CNN is lacking in research about character classification in nat- ural images regarding the whole English alphabet. This thesis conducts an experi- ment where TensorFlow is used to construct a CNN that is trained and tested on the Chars74K dataset, with 15 images per class for training and 15 images per class for testing. This is done with the aim of achieving a higher accuracy than the non-CNN approach by de Campos et al. [1], that achieved 55:26%. The thesis explores data augmentation techniques for expanding the small training set and evaluates the result of applying rotation, stretching, translation and noise- adding. The result of this is that all of these methods apart from adding noise gives a positive effect on the accuracy of the network. Furthermore, the experiment shows that with a three layered convolutional neural network it is possible to create a character classifier that is as good as de Campos et al.’s. -
Integral Estimation in Quantum Physics
INTEGRAL ESTIMATION IN QUANTUM PHYSICS by Jane Doe A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mathematical Physics Department of Mathematics The University of Utah May 2016 Copyright c Jane Doe 2016 All Rights Reserved The University of Utah Graduate School STATEMENT OF DISSERTATION APPROVAL The dissertation of Jane Doe has been approved by the following supervisory committee members: Cornelius L´anczos , Chair(s) 17 Feb 2016 Date Approved Hans Bethe , Member 17 Feb 2016 Date Approved Niels Bohr , Member 17 Feb 2016 Date Approved Max Born , Member 17 Feb 2016 Date Approved Paul A. M. Dirac , Member 17 Feb 2016 Date Approved by Petrus Marcus Aurelius Featherstone-Hough , Chair/Dean of the Department/College/School of Mathematics and by Alice B. Toklas , Dean of The Graduate School. ABSTRACT Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. Blah blah blah blah blah blah blah blah blah blah blah blah blah blah blah. -
JETIR Research Journal
© 2019 JETIR June 2019, Volume 6, Issue 6 www.jetir.org (ISSN-2349-5162) IMAGE TEXT CONVERSION FROM REGIONAL LANGUAGE TO SPEECH/TEXT IN LOCAL LANGUAGE 1Sayee Tale,2Manali Umbarkar,3Vishwajit Singh Javriya,4Mamta Wanjre 1Student,2Student,3Student,4Assistant Professor 1Electronics and Telecommunication, 1AISSMS, Institute of Information Technology, Pune, India. Abstract: The drivers who drive in other states are unable to recognize the languages on the sign board. So this project helps them to understand the signs in different language and also they will be able to listen it through speaker. This paper describes the working of two module image processing module and voice processing module. This is done majorly using Raspberry Pi using the technology OCR (optical character recognition) technique. This system is constituted by raspberry Pi, camera, speaker, audio playback module. So the system will help in decreasing the accidents causes due to wrong sign recognition. Keywords: Raspberry pi model B+, Tesseract OCR, camera module, recording and playback module,switch. 1. Introduction: In today’s world life is too important and one cannot loose it simply in accidents. The accident rates in today’s world are increasing day by day. The last data says that 78% accidents were because of driver’s fault. There are many faults of drivers and one of them is that they are unable to read the signs and instructions written on boards when they drove into other states. Though the instruction are for them only but they are not able to make it. So keeping this thing in mind we have proposed a system which will help them to understand the sign boards written in regional language. -
Wen-Chieh Wu Technical LEAD · SOFTWARE Architect · FULL STACK Engineer
Wen-Chieh Wu TECHNiCAL LEAD · SOFTWARE ARCHiTECT · FULL STACK ENGiNEER [email protected] | jeromewu.github.io | jeromewu | wenchiehwu | jeromewus Summary Passionate problem solver, technology enthusiast, compassionate leader with 7+ years as software engineer and architect and 5+ years as technical lead in multidisciplinary environments. Excel in leadership, critical thinking, communication and software engineering & architecture . Strong skills in JavaScript (incl. React, Express), Golang, Docker, CI/CD pipelines and software architecture design. Major contributor of tesseract.js (24.8k+ stars) and ffmpeg.wasm (6.1k+ stars). Certified architecting, data engineering, big data and machine learning specializations in Google Cloud Platform. Work Experience ByteDance Singapore STAFF SOFTWARE ENGiNEER Aug. 2021 ‑ PRESENT INTELLLEX Singapore TECHNiCAL LEAD Apr. 2020 ‑ Jul. 2021 • Led a team of backend and frontend engineers to develop knowledge platform for law. • Led re‑architecture project which eliminates 10+ redundant services, boosts observability and flexibility of data analysis pipeline and reduce cost • Reduced 30% of AWS cost in 2 months • Succeed in supporting to pass company ISO 27001 annual audit without any NC. Delta Electronics Taipei City, Taiwan SOFTWARE ARCHiTECT & PRODUCT MANAGER May 2019 ‑ Mar. 2020 • Established a cross‑region project team with 10+ members to research and develop an edge computing solution in manufacturing industry. • Designed a microservice software architecture for edge computing solution to enable flexiblity and scalibility. • Adopted gitlab‑CI and Ansible to deploy microservices in Kubernetes cluster to minize deployment efforts. • Developed a tensorflow serving like interface library in Golang. SENiOR TECHNiCAL LEAD Feb. 2018 ‑ May 2019 (1 year 4 months) • Established a corss‑region team of engineers, designers and QA with 20+ members in charge of front‑end development. -
Multilingual String Verification for Automotive Instrument Cluster Using Artificial Intelligence
WHITE PAPER www.visteon.com Multilingual String Verification for Automotive Instrument Cluster Using Artificial Intelligence Multilingual string verification for automotive instrument cluster Using Artificial Intelligence Deepan Raj M a, Prabu A b Software Engineer at Visteon Technical & Services Centre, Chennai a Technical Profession at Visteon Technical & Services Centre, Chennai b Abstract: Validation of HMI contents in Driver information system, In-Vehicle Infotainment, and Centre media Display is a big challenge as it prone human manual testing errors. Automating the text verification for multi languages and horizontal/vertical scrolling text is difficult challenge as the intelligence needed to achieve is high. To mitigate this effect vision based machine/deep learning algorithms will be implemented in such a way that three important applications have been created which serves to be the mother code for all the features that involves text as it main component of automated testing. They are 1. Multilingual text verification at various illuminations, grade out conditions and various background gradients using Opencv and Tesseract-OCR. 2. Horizontal & Vertical scrolling text using image key point stitching. 3. Automatic region of interest generation for text regions in the message center display using inception v3 deep neural network architecture. With the power of artificial intelligence in validating text makes it easier to automate with greater accuracy and can also be implemented in other areas like User Setting Menu traversal verification, Clock verification and much can be automated with less time and higher accuracy. Keywords: Computer Vision, Machine Learning, Deep learning, Neural Networks, OCR, automating validation. 1. INTRODUCTION: In recent years there has been a drastic improvement in the field of automobile, all the analog and semi digital clusters are being changed to full digital cluster, and lot of driver assisting feature are being added as the days goes on. -
Android Optical Character Recognition
Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-4, 2017 ISSN: 2454-1362, http://www.onlinejournal.in Android Optical Character Recognition 1 2 3 Shital Malhar , Manasi Gosavi , Pooja Lad 1,2,3 Dilkap Research Institute of Engineering and Management Studies, Neral. (Mumbai University) operating system which can run on every mobile Abstract - The next generation open operating device and not for their specific mobile devices systems are not on desktops or mainframes but on itself. This enables them to reach as many people as the small mobile devices people carry every day. possible. This application is useful for native The openness of these new environments leads to Tourists and Travellers who possess Android Smart new applications and markets and enables greater phones. The main objective of this application is to integration. Every day a Smartphone user may look help tourist to travel easily and freely without any for a new application dedicated for his need. difficulty. The proposed application also provides Android makes it easier for consumers to get and currency convertor, a real market value. use new content and applications on their Smart phones. The Proposed project presents an 1.1 Problem Definition extremely on-demand, fast and user friendly Android Application. This application is useful for The Project presents an extremely on-demand, fast native Tourists and Travellers who possess Android and user friendly Android Application. This Smart phones. One of the feature in application is it application is useful for native Tourists and enables Travellers and Tourists to easily capture Travelers who possess Android Smart phones.