Automated Processing of Multiple-Brightness Peak Histogram Image Using Curvature and Variance Estimation

DOI

10.2991/jrnal.2016.3.1.13How to use a DOI?

Keywords

Image processing, Histogram, Curvature, Variance estimation, Histogram matching, HMGD

Abstract

Previously, we have illustrated that the Histogram Matching based on Gaussian Distribution (HMGD) is an effective automated image processing method for obtaining a better feeling impression image. However, the simple HMGD works only for the image whose histogram has just one peak. For the image whose histogram has multiple-brightness peak, it does not work as in the case of single peak histogram image. In this paper, we propose the improved method for multiple-brightness peak (HMGD-MBP). This method can not only detect multiple peaks but also estimate the variance of Gaussian distribution at each detected peak in the image histogram, using curvature computation. This paper also presents the effectiveness of the proposed method by showing the experimental results.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Yusuke Kawakami
AU  - Tetsuo Hattori
AU  - Yoshiro Imai
AU  - Yo Horikawa
AU  - Kazuaki Ando
AU  - R. P. C. Janaka Rajapakse
PY  - 2016
DA  - 2016/06/01
TI  - Automated Processing of Multiple-Brightness Peak Histogram Image Using Curvature and Variance Estimation
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 55
EP  - 60
VL  - 3
IS  - 1
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2016.3.1.13
DO  - 10.2991/jrnal.2016.3.1.13
ID  - Kawakami2016
ER  -