Articolo in rivista, 2004, ENG, 10.1016/j.infrared.2004.03.012

Statistical analysis of IR thermographic sequences by PCA

S. Marinetti; E. Grinzato; P.G. Bison; E. Bozzi; M. Chimenti; G. Pieri; O. Salvetti

CNR-Istituto per le Tecnologie della Costruzione - Sede di Padova, Padua, Italy; CNR-Istituto per le Tecnologie della Costruzione - Sede di Padova, Padua, Italy; CNR-Istituto per le Tecnologie della Costruzione - Sede di Padova, Padua, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy

Automatic processing of IR sequences is a desirable target in Thermal Non Destructive Evaluation (TNDE) of materials. Unfortunately this task is made difficult by the presence of many undesired signals that corrupt the useful information detected by the IR camera. In this paper the Principal Component Analysis (PCA) is used to process IR image sequences to extract features and reduce redundancy by projecting the original data onto a system of orthogonal components. As a thermographic sequence contains information both in space and time, the way of applying PCA to these data cannot be straightforwardly borrowed from typical applications of PCA where the information is mainly spatial (e.g. Remote Sensing, Face Recognition). This peculiarity has been analysed and the results are reported. Finally, in addition to the use of PCA as an unsupervised method, its use in a 'learning and measuring' configuration is considered.

Infrared physics & technology 46 (1-2), pp. 85–91

Keywords

Algorithms, Cameras, Eigenvalues and eigenfunctions, Error analysis, IR image sequence, Principal component analysis, Learning and measuring, Data compression, Feature extraction

CNR authors

Bozzi Edoardo, Chimenti Massimo, Marinetti Sergio, Grinzato Ermanno, Pieri Gabriele, Salvetti Ovidio, Bison Paolo

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 43778

Year: 2004

Type: Articolo in rivista

Creation: 2009-06-16 00:00:00.000

Last update: 2023-07-17 11:53:26.000

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:43778

DOI: 10.1016/j.infrared.2004.03.012

ISI Web of Science (WOS): 000225208300012

Scopus: 2-s2.0-7544237271