Edge Detection Combined with Optical and Infrared NDT Techniques: an Aid for Wooden Samples with Complex Surface and Subsurface Defects

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1 13th International Symposium on Nondestructive Characterization of Materials (NDCM-XIII), May 2013, Le Mans, France More Info at Open Access Database Edge Detection Combined with Optical and Infrared NDT Techniques: an Aid for Wooden Samples with Complex Surface and Subsurface Defects Stefano SFARRA 1, Jean-Luc BODNAR 2, Dario AMBROSINI 1, Kamel MOUHOUBI 2, Domenica PAOLETTI 1 1 Las.E.R. Laboratory, Department of Industrial and Information Engineering and Economics (DIIIE), University of L Aquila, I-67100, Monteluco di Roio, L Aquila (AQ), Italy Phone: , Fax: ; {stefano.sfarra, dario.ambrosini, domenica.paoletti}@univaq.it 2 GRESPI/ECATHERM, UFR Sciences Exactes et Naturelles, BP 1039, Reims cedex 02, France; {jl.bodnar, kamel.mouhoubi}@univ-reims.fr Abstract To explore wood is to realize its complexity, its diversity, and its variability. The union of wood and paint is as old as the human desire to protect an object, or simply to decorate a surface. The link between paint and wood is therefore at the heart of any approach to conservation of these objects. Panel paintings are increasingly being investigated using advanced non-destructive infrared and optical measurement techniques. In the present work, a wooden sample having a complex surface and realized following the Cennino Cennini rules, containing natural and fabricated defects (Mylar inserts), was investigated by stimulated thermography, near-infrared reflectography, double-exposure (DE) and sandwich holographic (SH) interferometry. The stimulated thermography technique consists in depositing energy, whatever be the means of deposition and the type of energy (sun, flash lamp, laser, and hot air flow), into the observed system (in the present case a wooden sample with complex surface and subsurface defects) and in monitoring the temporal and/or local evolution of the surface temperature field of the system caused by this thermal stimulation. Infrared reflectography is a non-destructive testing imaging technique based on the different optical behaviour of visible and near-infrared (NIR) radiation through a thin pictorial layer. This effect is a consequence of both lower NIR absorption and reduced NIR scattering due to the particle size smaller than the wavelength. The acquisition of NIR images using LED lamps working at different wavelengths, seems a very promising method in this field. However, NIR and DE are not dynamic techniques, while SH is a dynamic technique. In the latter, a number of holograms can be made, each one recording a single state of the object, in a temporal sequence. Since enhancing the edge of a detached area identified by SH, means improving the detection of the defect s position, this idea was applied in the present research. Instead, the defect s depth was retrieved working with phase analysis, i.e. using the pulsed phase thermography (PPT) technique. Finally, the results coming from optical and infrared NDT techniques were compared each other in order to explore the advantages and disadvantages of the methods used. Keywords: Infrared thermography,near-infrared,holographic interferometry,panel painting,defect 1. Introduction The Laser Laboratory (currently Las.E.R., i.e. Laser & Electro optical Research in engineering metrology), founded in the early 70s by Professor Franco Gori can be considered as a pioneer laboratory in the field of optical non-destructive testing (NDT) techniques applied for the characterization, evaluation and preventive diagnostics of artistic and architectonical heritages [1-2]. In the same time, also the GRESPI/ECATHERM has a long tradition in the inspection of cultural heritages by thermal methods [3-4]. The integration of various NDT techniques for the detection of subsurface defects positioned at different depths in objects having a particular artistic value, currently seems the only method to reduce the risk of false alarms as well as to produce a useful map of the defects for the restorers. Starting from this point, the collaboration among international research groups involved in this field, can be considered an intelligent model to enhance the quality of the restoration phase both for the in situ inspections and for movable objects [5-6]. The sample inspected in the present work is a movable object that has the structure of a panel painting but with a complex surface. It was inspected using: 1) a multispectral approach involving the near-infrared reflectography, the ultraviolet, the visible and the long-infrared spectra, 2) holographic interferometry both in

2 the double-exposure and in the sandwich version. In the latter case, the Canny edge detection technique has been used in order to improve the quality of the fringes' contrast that appear above the Mylar inserts, simulating detachment areas, or to define the cracks' position. In addition, thermographic data was improved using principal component thermography (PCT) and pulsed phase thermography (PPT) algorithms [7-8], while the depth of the defects was retrieved thanks to the phase analysis [9]. 2. Description of the sample Panel paintings are composite structures incorporating wood, hidden glue, gesso composed of glue and gypsum (calcium sulphate) or chalk (calcium carbonate), paints and resin varnishes. Paint media can include wax, egg tempera, oils, and their combinations [10]. Panel paintings structure can also vary in complexity, the simplest consisting of paint applied directly to wood [11]. According to the rules of Italian ateliers in the 13 th and 14 th centuries, the canvas is glued to the wood, and then a gesso ground is applied above the canvas as a basis for paints and varnish. Therefore, panel paintings can be considered as a layered structure [12]. The inspected sample is an hollow cylinder [height (l): 180 mm] that is composed of a support in poplar wood [thickness (r r i ): 16.5 mm], several defects in Mylar [thickness: 0.2 mm], a layer of gypsum [thickness: 2 mm, α = 4.7 m 2 /s x 10-7 ] and a layer of paint [thickness: 0.5 mm, α = 0.87 m 2 /s x 10-7 ]. The layers of paint and gypsum are given by r e r (Figure 1a). In particular, the defects of the α side are five (Figure 1b), while the defects of the β side (Figure 1c) are seven, ranging from 10 mm of diameter (α 4 ) to 4.5 x 2 mm 2 (α 2 ). α 1 β 1 β 2 α 2 β 3 β 4 α 3 α 5 α 4 β 5 β 6 (a) (b) (c) Figure 1. (a) sketch of the sample, (b) α side. The position of the defects are marked, and (c) β side. The position of the defects are marked. In Figs. 1b,c the Readers can see the gypsum layer, while in Fig. 2a the painted sample. 3. Principles of non-destructive testing (NDT) In this Section the main principles of the non-destructive testing used are reported. The approaches in the 3.1 and 3.2 Sections have been divided just for reasons inherent the equipment used. β 7

3 3.1 Stimulated infrared thermography The principle of the stimulated infrared thermography is relatively simple. It consists in subjecting the sample to be analyzed in a flow of photons whose absorption produces a local rise of temperature in the neighbourhood of the luminous impact point, then to observe the variations of material s emission by means of an infrared camera. The thermo-physical phenomena mainly implemented by this testing procedure are the conduction and the thermal radiation. The photo-thermal signal collected by the infrared radiometer thus depends on parameters governing these physical phenomena (thermal conductivity, thermal diffusivity, emissivity, temperature, specific heat, density), but also on all the parameters being able to be correlated to these last ones (aspect of surface, presence of detachment, presence of crack, progress of a physico-chemical transformation, a drying, a sedimentation) [3-4]. In this inspection procedure, a FLIR SC 655 infrared camera together with a couple of C infrared lamps were used. 3.2 Active infrared thermography In this study, the sample surface was stimulated with a square heat pulse, while the heating up and the cooling down processes were recorded with a long-wave infrared camera from FLIR (ThermaCAM S65 HS, spectral band: µm, 320x256 pixels) [13]. The acquired data was then processed to improve defect contrast and signal-to-noise ratio, using: pulsed phase thermography (PPT) which transform data from time domain to the frequency domain in order to obtain the phase delay images or phasegrams that have an improved defect contrast, and principal component thermography (PCT) which reorganizes data into new components that take into account the main spatio-temporal variance of the sequence [7-8]. 3.3 Near-infrared reflectography (NIRR) NIRR essentially utilizes the radiation of electromagnetic spectrum immediately after the visible region between 0.7 and 1.1 µm. Due to the lower attenuation, these waves penetrate deeper into materials than electromagnetic waves of the visible band, and can aid in deciphering the features hidden under opaque layers of material. Most paints used for art purposes become more transparent when observed in longer wavelengths [14]. In particular, underdrawing visibility is a function of the transparency of the paint layers to NIR radiation and of the underdrawing contrast: IR absorption is high when carbon is present in the drawing (charcoal, graphite, carbonaceous pencils and inks), otherwise iron-gallium-based inks are transparent in the NIR spectrum, hence underdrawing painted with this material would not be detected, even if the paint layer is transparent. Reflectivity is high when the preparation is chalk-and-gypsum based. In this inspection procedure a CMOS camera (Canon 40DH 22.2 x 14.8 mm 10 megapixel, spectral band: µm), with several cut-off filters to limit the spectrum at a specific wavelength was used. Two PHILIPS IR 250S lamp that cover the near-infrared spectrum were employed as light sources (Figs. 2b-d). Otherwise, LED lamps working at 850 nm and 940 nm were employed without any filter mounted on the camera (Figs. 2f,g). 3.4 Ultraviolet (UV) imaging Ultraviolet (UV) imaging has begun to emerge as an inspection modality for some industrial and non-industrial processes. Ultraviolet light interacts with materials in a unique way,

4 enabling features and characteristics to be observed that are difficult to detect by other methods. Ultraviolet light tends to be strongly absorbed by many materials, making it possible to visualize the surface topology of an object without the light penetrating into the interior. Because of its short wavelength, it tends also to be scattered by surface features that are not apparent at longer wavelengths. Thus, ever smaller features can be resolved or detected via UV light scattered off of them. Reflected-UV imaging starts with the illumination of a surface with ultraviolet light. The UV light is reflected or scattered and is then imaged by a camera that is sensitive in the UV band [15]. The wavelength of the UV light is not shifted during the process. In this inspection procedure, the same camera illustrated in the Section 3.3 was used (Fig. 2e). 3.5 Holographic interferometry (HI) HI is a well known tool in NDE [16]. In double-exposure (DE) HI two holograms are recorded on the same plate, with each one capturing the object in a different state separated by a fixed time interval. This technique is less critical than real time (RT) holography because the two interfering waves are always reconstructed in exact register, and the fringes have a good contrast. However, DE HI is not dynamic and information on intermediate states of the test object is lost. Sandwich holography or, more precisely sandwich HI is a particular ingenious form of holographic interferometry based on the concept of recording two exposures on different plates. This technique gives more versatility to the DE set up; instead of making a DE on one holographic plate, the two exposures are made on different plates which are, then, combined in a plate holder. The image, reconstructed from a sandwich hologram gives the same fringes of a conventional DE hologram but, by having the images on two different plates, it is possible to manipulate them, by shifting and tilting, and hence the fringe pattern. There are several advantages in using this version of HI. For example, a number of holograms can be made, each one recording a single state of the test section, in a temporal sequence. Afterwards, the plates can be combined in pairs as desired, allowing one to compare any two hologram plates to study interferometrically any changes in the test object, in order to have a quasi continuous monitoring of the deformation. Probably, the most important advantage of SH is the possibility to eliminate unwanted fringes, caused by rigid body motion of the object investigated, with an a posterior manipulation of the fringe pattern [17]. There are of course some disadvantages: the plates have to be repositioned with high accuracy during reconstruction; the freedom of fringe manipulation also contains the seeds of possible errors. A correct use of the technique generally requires a specially designed holographic plate holder. Finally, a stressing technique must be devised in such a way that the anomalies induce detectable perturbations in the surface deformation. The hollow cylinder was analyzed using a short thermal irradiation provided by two Philips 250 IR lamps, which raises the surface temperature of some degrees Canny edge detector The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images. An optimal edge detector means: 1) good detection: the algorithm should mark as many real edges in the image as possible; 2) good localization: edges marked should be as close as possible to the edge in the real image, 3) minimal response: a given edge in the image should only be marked once, and where possible, image should not create false edges. To satisfy these requirements Canny used the calculus of variations a technique which finds the function which optimizes a given functional. The

5 optimal function in Canny s detector is described by the sum of four exponential terms, but it can be approximated by the first derivative of a Gaussian [18]. 4. Experimental results Seeing the NIR and UV results inherent the α side (Figs. 2b-g) and comparing them with the VIS image (Fig. 2a), no information can be retrieved about the preparatory drawing and the author s signature, that is positioned at the bottom right corner of this side. (a) (b) (c) (d) (e) (f) (g) Figure 2. (a) the painted sample; NIR result working with a filter at: (b) 715 nm, (c) 850 nm, (d) 1000 nm; (e) UV result; NIR result working with a LED lamp at: (f) 850 nm, (g) 940 nm. More information about the inner defects linked to the α and β sides are identifiable using the stimulated infrared thermography approach (Figs. 3a,b). In fact, all the defects (from α 1 to α 5 )

6 are detected in Fig. 3a, while two subsurface defects (β 1 and β 4, i.e. the smaller defects of the β side) are not detectable in Fig. 3b. Very interesting to note: 1) the presence of two unknown defects, surrounded by red dotted ovals in Fig. 3b, probably located inside the wooden support, and 2) the red colour of the α 5 defect (Fig. 3a) if compared to the other defects. α 1 β 2 α 2 β 3 α 3 α 4 β 5 β6 α 5 β 7 (a) (b) Figure 3. Stimulated infrared thermography results: (a) α side, and (b) β side. A comparison among NDT has involved the use of the DE (Figs. 4a,b) and SH techniques with the latter pattern of fringes enhanced by the Canny edge detector (Figs. 4c,d). α 3 α 3 (a) (b) (c) (d)

7 α 2 α 1 β 5 β 3 β 2 α 5 β 6 β 7 (e) (f) Figure 4. α side: (a) 1 st configuration: DE-HI t exp = 3 s heating time = 4 min, (b) 2 nd configuration: DE-HI t exp = 3 s heating time = 3 min; β side: (c) 1 st configuration: SH-HI, (d) 2 nd configuration: SH-HI; α side: (e) PCT-EOF4, β side: (f) PCT-EOF3. Several fabricated defects can be detected using the integrated approach, as well as the use of the Canny s algorithm (Fig. 4c,d) seems very promising to exalt the position and the shape of the defects, if compared to the classical DE holographic recording (Figs. 4a,b). Instead, comparing the results proposed in Fig. 3a and in Fig. 4e, the stimulated infrared thermography method appears more suitable to retrieve all the subsurface defects; also in the latter case, an interesting link is due to the α 5 defect characterized to a bright spot, i.e. the most visible defect detected. The same consideration is adapt to link the β 3 and β 7 defects of the β side (Figs. 3b and 4f). Since the depth of the defects are known and identical, i.e. they are located 2.5 mm beneath the paint surface, the defect s depth was also calculated from a relationship of the form [19]: α c z = C1 µ = C1 (1) π f where f b [Hz] is the blind frequency defined as the limiting frequency at which a defect located at a particular depth presents enough (phase or amplitude) contrast to be detected on the frequency spectra. Defect contrast is enhanced using the phase allowing deeper probing. Conventional experimental C 1 values when using the phase from lock-in thermography experiments range between 1.5 to more than 2 with a value of C 1 = 1.82 typically adopted in experimental studies [20]. PPT results agree with these numbers. In this way, the inversion problem in PPT is reduced to the estimation of f b from the phase, while α can be considered as a combined diffusivity (α c ), according to [21]: m α = = 4 10 (2) c 3 ( ) 10 s It is well-known that noise content present in phase data is considerable, especially at high frequencies. This causes a problem for the determination of the blind frequency. A de-noising step is therefore often required. The combination of PPT and TSR has proven to be very effective for this matter, reducing noise and allowing the depth retrieval for a defect (Fig. 5). Taking into account the data obtained working with the phase, as well as the input data, i.e. t = 1 s, heating time = 300 s, cooling time = 900 s, processed thermograms = 600, f max = 0.5 Hz, f b = 0.07 Hz, the estimated depth is 2.4 mm, very close to the real depth. b

8 (a) (b) (c) (d) (e) (f) Figure 5. α side: (a) thermogram at t = 3 s with cold image subtracted, (b) temperature evolution for two reference points marked in (a), (c) phase contrast curve: ϕ = ϕ defected ϕ sound, (d) phasegram at f = Hz linked to the red square detail in (a), (e) thermographic signal reconstruction (TSR) 5 th order, and (f) phase-frequency curve. α 3 defect, surrounded by a white dotted oval in Figs. 3a and 4a,b, was chosen as the reference defect for the depth retrieval with the phase, considering the difficulty of detecting its position using the PCT technique. 5. Conclusions In the cultural heritage field, there is an interest in inspecting objects having a complex surface [22]. From the present research, several conclusions can be drawn: a) the large amounts of energy absorbed by the carbon of the pigments used in the drawing is testified from the results of Fig. 2 and taking into account that the underdrawings were realized using graphite, b) the processing of the data inherent the stimulated infrared thermography approach, it is very effective in order to retrieved the position of the subsurface defects, c) the use of the Canny s algorithm on the SH results can be considered an interesting application both to enhance the contrast of the fringes pattern and to underline the shape of the defects, d) the integration between the PCT technique and the stimulated infrared thermography method has been able to characterize the presence of the α 5 defect as dissimilar to the other defects at least in the nature, e) the deviation [% error = 4% = (z est z)/z] between the real depth of the defects and the depth retrieved with the phase analysis provides a useful information to the restorer before the starting of the restoration procedure. References 1.S Amadesi, F Gori, R Grella and G Guattari, 'Holographic methods for painting diagnostics', Appl Optics, Vol 13, pp , S Amadesi, A D Altorio and D Paoletti, 'Double exposure speckle-hologram for strain measurements in frescoes diagnostics', Opt Commun, Vol 48, pp , J-L Bodnar, J-C Candorè, J-L Nicolas, G Szatanik, V Detalle and J-M Vallet, 'Stimulated infrared thermography applied to help restoring mural paintings', NDT&E Int, Vol 49, pp 40-46, 2012.

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