NESP: Nonlinear enhancement and selection of plane for optimal segmentation and recognition of scene word images

Deepak Kumar; M. N. Anil Prasad; A. G. Ramakrishnan

doi:10.1117/12.2008519

4 February 2013 NESP: Nonlinear enhancement and selection of plane for optimal segmentation and recognition of scene word images

Deepak Kumar, M. N. Anil Prasad, A. G. Ramakrishnan

Author Affiliations +

Proceedings Volume 8658, Document Recognition and Retrieval XX; 865806 (2013) https://doi.org/10.1117/12.2008519
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

In this paper, we report a breakthrough result on the difficult task of segmentation and recognition of coloured text from the word image dataset of ICDAR robust reading competition challenge 2: reading text in scene images. We split the word image into individual colour, gray and lightness planes and enhance the contrast of each of these planes independently by a power-law transform. The discrimination factor of each plane is computed as the maximum between-class variance used in Otsu thresholding. The plane that has maximum discrimination factor is selected for segmentation. The trial version of Omnipage OCR is then used on the binarized words for recognition. Our recognition results on ICDAR 2011 and ICDAR 2003 word datasets are compared with those reported in the literature. As baseline, the images binarized by simple global and local thresholding techniques were also recognized. The word recognition rate obtained by our non-linear enhancement and selection of plance method is 72.8% and 66.2% for ICDAR 2011 and 2003 word datasets, respectively. We have created ground-truth for each image at the pixel level to benchmark these datasets using a toolkit developed by us. The recognition rate of benchmarked images is 86.7% and 83.9% for ICDAR 2011 and 2003 datasets, respectively.

Citation Download Citation

Deepak Kumar, M. N. Anil Prasad, and A. G. Ramakrishnan "NESP: Nonlinear enhancement and selection of plane for optimal segmentation and recognition of scene word images", Proc. SPIE 8658, Document Recognition and Retrieval XX, 865806 (4 February 2013); https://doi.org/10.1117/12.2008519

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available