Abstract
This paper deals with the problem of processing solar images using a visual saliency based approach. The system consists of two main parts: 1) a pre-processing part carried out by using an enhancement method that aims at highlighting the Sun in solar images and 2) a visual saliency based approach that detects active regions (events of interest) on the pre-processed images. Experimental results show that the proposed approach exhibits a precision index of about of 70% and thus it is, to some extent, suitable to allow detection of active regions, without human assistance, mainly in massive processing of solar images. However, the recall performance points out that at the current stage of development the method has room for improvements in detecting some active areas, as shown the F-score index that at presently is about 60%.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Rubio da Costa, F.: Chromospheric Flares: Study of the Flare Energy Release and Transport. PhD thesis, University of Catania, Catania, Italy (2010)
Durak, N., Nasraoui, O.: Feature exploration for mining coronal loops from solar images. In: Proceedings of the 20th IEEE International Conference on Tools with Artificial Intelligence, Washington, DC, USA, vol. 1, pp. 547–550 (2008)
Faro, A., Giordano, D., Spampinato, C.: An automated tool for face recognition using visual attention and active shape models analysis, vol. 1, pp. 4848–4852 (2006)
Giordano, D., Leonardi, R., Maiorana, F., Scarciofalo, G., Spampinato, C.: Epiphysis and metaphysis extraction and classification by adaptive thresholding and DoG filtering for automated skeletal bone age analysis. In: Conf. Proc. IEEE Eng. Med. Biol. Soc., pp. 6552–6557 (2007)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning, 1st edn. Addison-Wesley Longman Publishing Co., Inc., Boston (1989)
Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(11), 1254–1259 (1998)
Liu, W., Tong, Q.Y.: Medical image retrieval using salient point detector, vol. 6, pp. 6352–6355 (2005)
McAteer, R., Gallagher, P., Ireland, J., Young, C.: Automated boundary-extraction and region-growing techniques applied to solar magnetograms. Solar Physics 228, 55–66 (2005)
Qu, M., Shih, F.Y., Jing, J., Wang, H.: Solar flare tracking using image processing techniques. In: ICME, pp. 347–350 (2004)
Rust, D.M.: Solar flares: An overview. Advances in Space Research 12(2-3), 289–301 (1992)
Spampinato, C.: Visual attention for behavioral biometric systems. In: Wang, L., Geng, X. (eds.) Behavioral Biometrics for Human Identification: Intelligent Applications, ch. 14, pp. 290–316. IGI Global (2010)
Tong, Y., Konik, H., Cheikh, F.A., Guraya, F.F.E., Tremeau, A.: Multi-feature based visual saliency detection in surveillance video, vol. 7744, p. 774404. SPIE, CA (2010)
Walter, D.: Interactions of Visual Attention and Object Recognition: Computational Modeling, Algorithms, and Psychophysics. PhD thesis. California Institute of Technology,Pasadena, California (2006)
Zharkova, V., Ipson, S., Benkhalil, A., Zharkov, S.: Feature recognition in solar images. Artif. Intell. Rev. 23, 209–266 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cannavo, F., Spampinato, C., Giordano, D., Rubio da Costa, F., Nunnari, S. (2011). Detection of Active Regions in Solar Images Using Visual Attention. In: Cherifi, H., Zain, J.M., El-Qawasmeh, E. (eds) Digital Information and Communication Technology and Its Applications. DICTAP 2011. Communications in Computer and Information Science, vol 166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21984-9_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-21984-9_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21983-2
Online ISBN: 978-3-642-21984-9
eBook Packages: Computer ScienceComputer Science (R0)