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Image Compression and Video Segmentation Using Hierarchical Self-Organization

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Abstract

Both image compression based on color quantization and image segmentation are two typical tasks in the field of image processing. Several techniques based on splitting algorithms or cluster analyses have been proposed in the literature. Self-organizing maps have been also applied to these problems, although with some limitations due to the fixed network architecture and the lack of representation in hierarchical relations among data. In this paper, both problems are addressed using growing hierarchical self-organizing models. An advantage of these models is due to the hierarchical architecture, which is more flexible in the adaptation process to input data, reflecting inherent hierarchical relations among data. Comparative results are provided for image compression and image segmentation. Experimental results show that the proposed approach is promising for image processing, and the powerful of the hierarchical information provided by the proposed model.

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Notes

  1. http://mmc36.informatik.uni-augsburg.de/VSSN06_OSAC

  2. http://www.cvg.cs.rdg.ac.uk/PETS2001/pets2001-dataset.html

  3. http://www.cs.cmu.edu/~yaser/GroundtruthSeq.rar

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Acknowledgments

This work is partially supported by the Ministry of Economy and Competitiveness of Spain under grant TIN2011-24141, project name Detection of anomalous activities in video sequences by self-organizing neural systems, and the Autonomous Government of Andalusia (Spain) under project P12-TIC-6213, project name Development of Self-Organizing Neural Networks for Information Technologies.

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Authors and Affiliations

  1. Department of Computer Science, E.T.S.I. Informatica, University of Malaga, Bulevar Louis Pasteur n 35, 29071 , Malaga, Spain

    Esteban J. Palomo, Enrique Domínguez, Rafael M. Luque-Baena & José Muñoz

Authors
  1. Esteban J. Palomo
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  2. Enrique Domínguez
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  3. Rafael M. Luque-Baena
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  4. José Muñoz
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Correspondence to Esteban J. Palomo.

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Palomo, E.J., Domínguez, E., Luque-Baena, R.M. et al. Image Compression and Video Segmentation Using Hierarchical Self-Organization. Neural Process Lett 37, 69–87 (2013). https://doi.org/10.1007/s11063-012-9266-5

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