Patch Autocorrelation Features for Optical Character Recognition

Radu Tudor Ionescu, Andreea-Lavinia Popescu, Dan Popescu

2015

Abstract

The autocorrelation is often used in signal processing as a tool for finding repeating patterns in a signal. In image processing, there are various image analysis techniques that use the autocorrelation of an image for a broad range of applications from texture analysis to grain density estimation. In this paper, a novel approach of capturing the autocorrelation of an image is proposed. More precisely, the autocorrelation is recorded in a set of features obtained by comparing pairs of patches from an image. Each feature stores the euclidean distance between a particular pair of patches. Although patches contain contextual information and have advantages in terms of generalization, most of the patch-based techinques used in image processing are heavy to compute with current machines. Therefore, patches are selected using a dense grid over the image to reduce the number of features. This approach is termed Patch Autocorrelation Features (PAF). The proposed approach is evaluated in a series of handwritten digit recognition experiments using the popular MNIST data set. The Patch Autocorrelation Features are compared with the euclidean distance using two classification systems, namely the k-Nearest Neighbors and Support Vector Machines. The empirical results show that the feature map proposed in this work is always better than a feature representation based on raw pixel values, in terms of accuracy. Furthermore, the results obtained with PAF are comparable to other state of the art methods.

Paper Citation

in Harvard Style

Ionescu R., Popescu A. and Popescu D. (2015). Patch Autocorrelation Features for Optical Character Recognition . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 419-426. DOI: 10.5220/0005289804190426

in Bibtex Style

@conference{visapp15,
author={Radu Tudor Ionescu and Andreea-Lavinia Popescu and Dan Popescu},
title={Patch Autocorrelation Features for Optical Character Recognition},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={419-426},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005289804190426},
isbn={978-989-758-089-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Patch Autocorrelation Features for Optical Character Recognition
SN - 978-989-758-089-5
AU - Ionescu R.
AU - Popescu A.
AU - Popescu D.
PY - 2015
SP - 419
EP - 426
DO - 10.5220/0005289804190426