Untitled Download fulltext HTML
Caballero, R., Berbey, A., & Cogley, A. (2018). Segmentación de Imágenes Basada en Entropía de Pixel. KnE Engineering, 3(2), 523-531. https://doi.org/10.18502/keg.v3i1.1456

https://doi.org/10.18502/keg.v3i1.1456

statistics

  • 1074 Abstract Views
  • 1137 PDF Views
  • 0 HTML Views

authors

  • Rony Caballero

    Rony Caballero

    Universidad Tecnológica de Panamá, Ciudad de Panamá
  • Aránzazu Berbey

    Aránzazu Berbey

    Universidad Tecnológica de Panamá, Ciudad de Panamá
  • Alberto Cogley

    Alberto Cogley

    Universidad Tecnológica de Panamá, Ciudad de Panamá

Published Date

  • Feb 11, 2018

Segmentación de Imágenes Basada en Entropía de Pixel

KnE Engineering / 6th Engineering, Science and Technology Conference - Panama 2017 (ESTEC 2017) / Pages 523-531

Abstract

In this research, a new methodology for color image segmentation is proposed. In this approach, a pixel entropy derivative based rule is used. The algorithm is tested not only with good quality images, but also with some of them with light scattering and absortion problems.  Preliminary results shows good performance of this algorithm.

Keywords: Image processing, segmentation, entropy, feedback. 

References
[1] Grigorescu S., Ristić-Durrant D., Vuppala S. and Gräser A. (2008). “Closed-Loop Control in Image Processing for Improvement of Object Recognition”. Proceedings of the 17th World Congress of the International Federation of Automatic Control. Seoul, Korea, July 6-11, 2008


[2] Koik B. and Ibrahim H. (2013). “A Literature Survey on Blur Detection Algorithms for Digital Imaging”. 2013 First International Conference on Artificial Intelligence, Modelling & Simulation.


[3] Lei, X. and Fu A. (2008). “Two-Dimensional Maximum Entropy Image Segmentation Method Based on Quantum-behaved Particle Swarm Optimization Algorithm”. Fourth International Conference on Natural Computation.


[4] Peng W., Hongling X., Wenlin L. and Wenlong S. (2016). “Harris Scale Invariant Corner Detection Algorithm Based on the Significant Region”. International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.9, No.3 (2016), pp.413- 420.


[5] Ristić-Durrant D and Gräser D (2008). “Closed-Loop Control of Segmented Image Quality for Improvement of Digital Image Processing”. Automatic Control and Robotics Vol. 7, No 1, 2008, pp. 27 – 34.


[6] Sahoo P. and Arora G. (2004). “Thresholding method based on two-dimensional Renyi’s entropy”. Pattern Recognition 37 (2004) 1149 – 1161


[7] Szeliski R. (2010). “Computer Vision: Algorithms and Applications”. Springer 2010.


[8] Sun L., Wang S. and Xing J. (2014). “An Improved Harris Corner Detection Algorithm for Low Contrast Image”. The 26th Chinese Control and Decision Conference.