Thermography data fusion and nonnegative matrix factorization for the evaluation of cultural heritage objects and buildings

Abstract

The application of the thermal and infrared technology in different areas of research is considerably increasing. These applications involve Non-destructive Testing (NDT), Medical analysis (Computer Aid Diagnosis/Detection-CAD), and Arts and Archeology among many others. In the arts and archaeology field, infrared technology provides significant contributions in term of finding defects of possible impaired regions. This has been done through a wide range of different thermographic experiments and infrared methods. The proposed approach here focuses on application of some known factor analysis methods such as standard Non-Negative Matrix Factorization (NMF) optimized by gradient-descent-based multiplicative rules

Infrared Non-Destructive Testing via Semi-Nonnegative Matrix Factorization

“…The presented thermography analysis has been performed in a PC (Intel(R) Core(TM) i5 CPU, 3.20GHz, RAM 16.00GB, 64 bit Operating System) and using MATLAB computer programming. Figure 2 presents selected results of subsurface defect detection using semi-NMF computed by two computational methods: non-negative least square (SemiNMF-nnls, Figure 2h), and gradient descent rules (SemiNMF-Ruls, Figure 2i) and compared to the state-of-the-art approaches such as NMF (Figure 2a), PCT [8] (Figure 2b), NMF-gd (Figure 2c), NMF-nnls [6] (Figure 2d), Sparse-PCT [10] (Figure 2e), Candid Covariance-Free Incremental Principal Component Thermography (CCIPCT) [9] ( Figure 2g), and Sparse-NMF (Figure 2e) [12]. We selected k = 10 for most of this analyses corresponding to an 80% variance via decomposition method for all methods.…”

“…Matrix factorization has been used for infrared non-destructive testing (IR-NDT) and compared to PCA and archetypal analysis (AA) to assess its advantages and pitfalls as reported in [5]. This analysis continued in [6] where NMF was applied to cultural heritage objects and buildings using gradient descend (GD) and non-negative least square (NNLS) and demonstrating the good performance of such algorithms for detecting subsurface defects. Here, we present Semi-NMF using NNLS and based on gradient descent rule (Ruls) methods to detect subsurface defects in Aluminum.…”

Application of Sparse Non-Negative Matrix Factorization in infrared non-destructive testing

“…Matrix factorization has been employed for infrared non-destructive testing (IR-NDT) where showed the application of three methods: principal component analysis (PCA), non-negative matrix factorization (NMF), and archetypal analysis (AA) and showed its advantages and pitfalls [5]. Moreover, the application of NMF for two ways of its computations using gradient descend (GD) and non-negative least square (NNLS) for evaluating of cultural heritage objects and buildings illustrated considerable performance of such algorithm for detecting subsurface defects [6].…”

“…The presented thermography analysis has been performed in a PC (Intel(R) Core(TM) i5 CPU, 3.20GHz, RAM 16.00GB, 64 bit Operating System) and using MATLAB computer programming. Figure 1 presents selected results of the subsurface defect detection using Sparse-NMF (Figure 1.f) compared with state-of-the-art approaches such as PCT [8] (Figure 1.b), Candid Covariance-Free Incremental Principal Component Thermography (CCIPCT) [9] (Figure 1.g), NMF (Figure 1.a), NMF-gd (Figure 1.c), NMF-nnls [6] (Figure 1.d), and Sparse-PCT [10] (Figure 1.e). The qualitative results of Sparse-NMF indicated considerable accuracy relative to state-of-the-art techniques.…”

Combining InfraRed Thermography and UAV Digital Photogrammetry for the Protection and Conservation of Rupestrian Cultural Heritage Sites in Georgia: A Methodological Application

“…IRT, given the portability and the fast acquisition and processing times of thermographic data, can be profitably applied for mapping criticalities in the field of tangible CH conservation [76][77][78]. In Vardzia the obtained ST maps allowed to map the moisture sectors in correspondence to the large sub-vertical open fractures orthogonal to the valley, and where the main streams cut the whole breccia level.…”