scholarly journals Sixth Sense Technology with Optical Character Recognition

2021 ◽  
Vol 9 (VI) ◽  
pp. 3394-3397
Author(s):  
Niharika Tiwari
Keyword(s):  
Augmented Reality ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Actual World ◽  
Innovative Technology ◽  
Hand Gesture ◽  
Hand Motion ◽  
Optical Character ◽  
And Control ◽  
Human Kind

Sixth Sense Technology is an innovative technology that will be further developed in the future and will be used for the benefit of human kind. It depends on the ideas of augmented reality and has all around carried out the view of it. The thing that makes it special is the way all the technologies are combined together to get a beneficial output. It partners advances like hand motion acknowledgment, picture catching, preparing, and control, and so forth OCR is to achieve change or change of a book or text-containing documents, for instance, deciphered substance, printed or sifted text pictures, into an editable electronic plan for more significant and further planning. Along these lines, our Goal is to carry part of the actual world to computerized world. Hand Gesture Recognition is in great demand today and can be executed with sixth sense technology.

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 Automatic Number Plate Recognition System Using Optical Character Recognition

2019 ◽  
pp. 986-992 ◽  
Author(s):  
Monika Arora ◽  
Anubha Jain ◽  
Shubham Rustagi ◽  
Tushar Yadav
Keyword(s):  
Embedded System ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Recognition System ◽  
Traffic Monitoring ◽  
Monitoring And Control ◽  
Monitoring And Control System ◽  
Vehicle Owner ◽  
Optical Character ◽  
And Control

In the last few decades, the number of active vehicle population has increased drastically which has made it difficult for the authorities to keep a track of them as well as to identify the vehicle owner in case of any traffic violation. Automatic Number Plate Recognition System (ANPR) is a real-time machine-intelligent and embedded system which identifies the characters directly from the image of the number plate. Due to crucial research and development of technology and the increasing use of vehicles, the need for a machine-oriented recognition and monitoring system is of immense importance. The technology has become a major requirement and is playing a crucial role in a vast sea of applications related to automated transport monitoring and control system such as traffic monitoring, challan management, detection of stolen vehicles, electronic payment of tolls on highways or bridges, parking lots access control, etc. This technology requires extensive mobility and station flexibility which causes it to be installed on such hardware that is very mobile enough so that the operator can use it very efficiently. ANPR System through the use of Optical Character Recognition (OCR) makes the system to be used as an application on smartphones. This provides the operator to use the system and identify number plates by just capturing the image and processing by neural networks working in the background of OCR. The ANPR system as a whole will result in easy and safe monitoring of the traffic and to keep an easy record in case of any violation. Also, it will save individuals to save their time in standing at long queues at toll taxes and paying cash which will be done with the ANPR system and using E-wallet.

scholarly journals Evaluation of User Experience in Translator Applications (Banjar-Indonesian and Indonesian-Banjar) Based on Mobile Augmented Reality Technology using the UX Honeycomb Method

2021 ◽  
Vol 6 (1) ◽  
pp. 7-13
Author(s):  
Aulia Akhrian Syahidi ◽  
Herman Tolle
Keyword(s):  
Augmented Reality ◽  
User Experience ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Mobile Augmented Reality ◽  
Average Value ◽  
Optical Character ◽  
Augmented Reality Technology ◽  
Strongly Agree ◽  
The City

The translator application from Banjar Language to Indonesian is called BandoAR and vice versa from Indonesian to Banjar Language which is called NdoBAR. Both applications utilize Mobile Augmented Reality technology with the Optical Character Recognition (OCR) Method for word recognition in the detected image. This application is recommended and used to help tourists visiting the city of Banjarmasin to be able to understand the language used by local people as a means of communication and for the general public who want to know the peculiarities of the Banjar language itself. The purpose of this study was to evaluate the user experience of the BandoAR and NdoBAR applications. The method used is UX Honeycomb, which has seven aspects to assess the user experience of an application. A total of 50 respondents were presented to assess the two applications. The results showed that the BandoAR application had an average UX Honeycomb value of 4.91 with a Very Strongly Agree predicate and for the NdoBAR application, an average value of UX Honeycomb was 4.89 with a Very Strongly Agree predicate. Both applications have fulfilled aspects of the user experience. However, we need some fixes for the shortcomings of both apps, to continue to improve interactions, better user experience, and other smart capabilities.

scholarly journals Aplikasi Identifikasi Kata Berbasis Optical Character Recognition dan Augmented Reality

2019 ◽  
Vol 8 (2) ◽  
pp. 77-85
Author(s):  
Devy Normalasari ◽  
Irawan Afrianto
Keyword(s):  
Augmented Reality ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Optical Character

Teks tertulis merupakan salah satu metode yang umum untuk menyampaikan informasi. Namun, ketika berwisata ke luar negeri informasi tersebut ditemui dalam bahasa asing. Bagi beberapa individu perbedaan bahasa membuat informasi tersebut tidak dapat tersampaikan dengan baik. Penggunaan kamus digital menjadi pilihan wisatawan untuk menerjemahkan bahasa dengan pencarian kata yang cepat dan mudah. Namun kamus digital masih memiliki kekurangan, yaitu wisatawan harus mengetikan teks yang ingin diterjemahkan, maka dibutuhkan sebuah aplikasi alternatif yang dapat mendeteksi karakter teks dan menerjemahkannya langsung. Salah satu teknologi yang dapat dimanfaatkan adalah teknologi Augmented Reality dengan dukungan perangkat mobile bersistem operasi Android. Teknologi Optical Character Recognition juga akan diterapkan untuk pengenalan kata pada citra yang dideteksi. Pada sistem yang akan dibangun, Augmented Reality akan memanfaatkan kamera yang ada pada perangkat Android untuk mendeteksi teks tanpa harus menyimpan gambar terlebih dahulu. Kemudian objek atau target teks yang terdeteksi akan dikonversi kedalam teks yang dapat diedit oleh Optical Character Recognition sehingga teks tersebut dapat diterjemahkan. Penerjemahan dilakukan secara offline maupun online dengan Bing Miscrosoft Translator. Hasil terjemahan teks tersebut kemudian akan ditampilkan dengan Augmented Reality pada layar perangkat Android. Terjemahan kata akan tampil di luar wilayah pendeteksian atau ROI secara berurut untuk setiap kata dari atas ke bawah. Implementasi AR dengan OCR pada aplikasi Word Translatar diharapkan dapat membantu wisatawan dalam menerjemahkan kata-kata berbahasa asing secara realtime dan akurat tanpa harus mengetik. Kata kunci : Augmented Reality, Optical Character Recognition, Pengenalan Kata, Penerjemah, Vuforia

scholarly journals A usability evaluation of an interactive application for halal products using optical character recognition and augmented reality technologies

2017 ◽  
Author(s):  
Meng Chun Lam ◽  
Siti Soleha Muhammad Nizam ◽  
Haslina Arshad ◽  
Saidatul A’isyah Ahmad Shukri ◽  
Nurhazarifah Che Hashim ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Usability Evaluation ◽  
Optical Character ◽  
Interactive Application

A Structured Method for the Recognition of Complex Historical Tables

1997 ◽  
Vol 9 (1-3) ◽  
pp. 58-77
Author(s):  
Vitaly Kliatskine ◽  
Eugene Shchepin ◽  
Gunnar Thorvaldsen ◽  
Konstantin Zingerman ◽  
Valery Lazarev
Keyword(s):  
Nineteenth Century ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Complex Structure ◽  
Source Material ◽  
Historical Sources ◽  
Tax Assessment ◽  
Optical Character ◽  
Algorithmic Model ◽  
Machine Readable

In principle, printed source material should be made machine-readable with systems for Optical Character Recognition, rather than being typed once more. Offthe-shelf commercial OCR programs tend, however, to be inadequate for lists with a complex layout. The tax assessment lists that assess most nineteenth century farms in Norway, constitute one example among a series of valuable sources which can only be interpreted successfully with specially designed OCR software. This paper considers the problems involved in the recognition of material with a complex table structure, outlining a new algorithmic model based on ‘linked hierarchies’. Within the scope of this model, a variety of tables and layouts can be described and recognized. The ‘linked hierarchies’ model has been implemented in the ‘CRIPT’ OCR software system, which successfully reads tables with a complex structure from several different historical sources.

CNN-based Rain Reduction in Street View Images

2020 ◽  
Vol 2020 (1) ◽  
pp. 78-81
Author(s):  
Simone Zini ◽  
Simone Bianco ◽  
Raimondo Schettini
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
State Of The Art ◽  
Weather Conditions ◽  
Specific Interest ◽  
Optical Character ◽  
Street View ◽  
In The Wild ◽  
Bad Weather ◽  
Detection And Recognition

Rain removal from pictures taken under bad weather conditions is a challenging task that aims to improve the overall quality and visibility of a scene. The enhanced images usually constitute the input for subsequent Computer Vision tasks such as detection and classification. In this paper, we present a Convolutional Neural Network, based on the Pix2Pix model, for rain streaks removal from images, with specific interest in evaluating the results of the processing operation with respect to the Optical Character Recognition (OCR) task. In particular, we present a way to generate a rainy version of the Street View Text Dataset (R-SVTD) for "text detection and recognition" evaluation in bad weather conditions. Experimental results on this dataset show that our model is able to outperform the state of the art in terms of two commonly used image quality metrics, and that it is capable to improve the performances of an OCR model to detect and recognise text in the wild.

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