Journal of Computer Science and Engineering (JCSE)
Vol 2, No 2: August (2021)

Punjabi Text Recognition System for Portable Devices: A Comparative Performance Analysis of Cloud Vision API with Tesseract

Kaur, Ravneet (Unknown)
Sharma, Dharam Veer (Unknown)



Article Info

Publish Date
10 Aug 2021

Abstract

The increasing availability of high performance, low priced, portable digital imaging devices has created an opportunity for on demand analysis of documents. In this paper, Punjabi Text Recognition System is developed for portable devices using two different approaches that is Google’s Cloud Vision APIs and LSTM based Tesseract OCR Engine. The performance of developed mobile based systems is compared in term of runtime and recognition accuracy. Both Vision API and LSTM based OCR engine provides good results for Roman Based Scripts. Particularly for Gurmukhi text document images, Cloud Vision API recognizes Punjabi with good accuracy as compared to Tesseract. We presented a detailed comparison and computed the character and word level accuracy of both the systems for same set of images.

Copyrights © 2021






Journal Info

Abbrev

JCSE

Publisher

Subject

Computer Science & IT

Description

Computer Architecture, Processor design, operating systems, high-performance computing, parallel processing, computer networks, embedded systems, theory of computation, design and analysis of algorithms, data structures and database systems, theory of computation, design and analysis of algorithms, ...