1. Processing CsI(Tl) 2-D matrices by means of neural networks and Markov random fields
- Author
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Alderighi, Monica, Anzalone, Antonello, Baruzzi, Roberto, Cardella, Giuseppe, Cavallaro, Salvatore, De Filippo, Enrico, Geraci, Elena, Giustolisi, Francesco, Guazzoni, Paolo, Lanzalone, Gaetano, Lanzano, Gaetano, Pagano, Angelo, Papa, Massimo, Pirrone, Sara, Politi, Giuseppe, Porto, Francesco, Russo, Stefania, Sechi, Giacomo R., Sperduto, Leda, and Zetta, Luisa
- Subjects
Image processing -- Methods ,Neural networks -- Usage ,Markov processes -- Analysis ,Neural network ,Business ,Electronics ,Electronics and electrical industries - Abstract
This paper is concerned with the automatic analysis of data coming from the multidetector array CHIMERA, used in nuclear physics at intermediate energies. Each of Chimera's detection cells is a telescope made of a [DELTA]E silicon detector and a CsI(Tl) crystal, thick enough to stop all the charged light particles. The signals produced in the CsI(Tl) scintillators can be subdivided into two components--Fast and Slow. These data are collected in the form of bi-dimensional matrices (Fast-Slow matrices), particularly important for light particle identification. The proposed approach consists in applying image processing techniques. In particular, Grossberg's pre-attentive neural networks are used as a first step in order to isolate the regions of physical interest in the matrices and to roughly identify the directions depicted by the most intense lines; a successive step of filtering based on Markov random fields is then performed. Index Terms--Clustering methods, image processing, nuclear measurements, visualization.
- Published
- 2002