Design of an Optical Character Recognition System for Camera-based Handheld Devices

09/15/2011
by   Ayatullah Faruk Mollah, et al.
0

This paper presents a complete Optical Character Recognition (OCR) system for camera captured image/graphics embedded textual documents for handheld devices. At first, text regions are extracted and skew corrected. Then, these regions are binarized and segmented into lines and characters. Characters are passed into the recognition module. Experimenting with a set of 100 business card images, captured by cell phone camera, we have achieved a maximum recognition accuracy of 92.74 powerful OCR engine, present recognition accuracy is worth contributing. Moreover, the developed technique is computationally efficient and consumes low memory so as to be applicable on handheld devices.

READ FULL TEXT
research
01/03/2011

Segmentation of Camera Captured Business Card Images for Mobile Devices

Due to huge deformation in the camera captured images, variety in nature...
research
04/06/2010

Text/Graphics Separation for Business Card Images for Mobile Devices

Separation of the text regions from background texture and graphics is a...
research
08/28/2013

Text recognition in both ancient and cartographic documents

This paper deals with the recognition and matching of text in both carto...
research
07/02/2021

Optical Braille Recognition using Circular Hough Transform

Braille has empowered visually challenged community to read and write. B...
research
11/14/2019

Character Keypoint-based Homography Estimation in Scanned Documents for Efficient Information Extraction

Precise homography estimation between multiple images is a pre-requisite...
research
02/21/2010

Text/Graphics Separation and Skew Correction of Text Regions of Business Card Images for Mobile Devices

Separation of the text regions from background texture and graphics is a...
research
04/17/2020

Image Processing Based Scene-Text Detection and Recognition with Tesseract

Text Recognition is one of the challenging tasks of computer vision with...

Please sign up or login with your details

Forgot password? Click here to reset