Characterization of automotive paint by optical coherence tomography

Robotic-OCT guided inspection and microsurgery of monolithic storage devices

Data recovery from monolithic storage devices (MSDs) is in high demand for legal or business purposes. However, the conventional data recovery methods are destructive, complicated, and time-consuming. We develop a robotic-arm-assisted optical coherence tomography (robotic-OCT) for non-destructive inspection of MSDs, offering ~7 μm lateral resolution, ~4 μm axial resolution and an adjustable field-of-view to accommodate various MSD sizes. Using a continuous scanning strategy, robotic-OCT achieves automated volumetric imaging of a micro-SD card in ~37 seconds, significantly faster than the traditional stop-and-stare scanning that typically takes tens of minutes. We also demonstrate the robotic-OCT-guided laser ablation as a microsurgical tool for targeted area removal with precision of ±10 μm and accuracy of ~50 μm, eliminating the need to remove the entire insulating layer and operator intervention, thus greatly improving the data recovery efficiency. This work has diverse potential applications in digital forensics, failure analysis, materials testing, and quality control.

A novel approach for forensic identification of automotive paints using optical coherence tomography and multivariate statistical methods

Automotive paint is one of the most important evidence in solving vehicle-related criminal cases. It contains the critical information about the suspected vehicle, providing essential clues for the investigation. In this study, a novel approach based on optical coherence tomography combined with multivariate statistical methods was proposed to facilitate rapid, accurate and nondestructive identification of different brands of automotive paints. 164 automotive paint samples from 8 different manufacturers were analyzed by a spectral-domain optical coherence tomography system (SD-OCT). Two-dimensional cross-sectional OCT images and three-dimensional OCT reconstruction of vehicle paints of different paints were obtained to show the internal structural differences. Visual discrimination of A-scan data after registration and averaging processing was first used to distinguish different samples. An scanning electron microscope was utilized to obtain the cross-sectional image of the sample to evaluate the effectiveness of OCT technique. Then the original A-scan data, first derivative data and second derivative data of 136 paints with four layers from 7 different manufacturers were collected. Multivariate statistical methods, including principal component analysis (PCA), multi-layer perceptron (MLP), k-nearest neighbor (KNN) algorithm and Bayes discriminant analysis (BDA), were used to analyze different datasets. The results show the hybrid PCA and BDA model based on the first derivative OCT data achieved the best result of 100% accuracy on the testing dataset for identifying automotive paints. It is demonstrated that the OCT technique combined with multivariate statistics could be a promising method for identifying the automotive paints rapidly and accurately.

Structural and optical characterization of banknotes using spectral-domain optical coherence tomography

Counterfeiting of banknotes remains a severe threat to economic security and social stability. The characterization of banknote has mainly relied on the assessment of various security features applied to the surface of the note. However, the surface features are easy to forge and contain insufficient information to discover the source. In this paper, a novel approach for banknote characterization has been proposed by employing spectral-domain optical coherence tomography (SD-OCT) that can provide structural and optical features. Three groups of counterfeit Chinese 100 Yuan banknotes produced by different printing manners and one group of authentic banknotes were examined by SD-OCT without any sample preparation and four distinct areas were selected for imaging. High-resolution tomographic and three-dimensional (3D) volumetric OCT images were obtained and a set of features were first revealed to characterize the banknotes qualitatively and quantitatively. The results demonstrated that SD-OCT was effective to detect and classify different types of counterfeit banknotes and could potentially be used to link counterfeit banknotes to their sources in a fast, simple and nondestructive manner.

Discrimination of white automotive paint samples using ATR-FTIR and PLS-DA for forensic purposes

The consequences of a hit-and-run car crash are significant and may include serious injuries to the victims, health system overload and even victim's death. The vehicle and driver identification are often challenging for local law enforcement. The aim of this study was to develop a methodology to discriminate between automotive paint samples according to the make of the vehicle and its color shade. 143 white samples (collected at traffic accident scenes) were analyzed in situ by Fourier transform infrared spectroscopy with attenuated total reflectance (ATR-FTIR) and coupled microscopy. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed for data analysis. The samples were split into three groups: calibration set, validation set and external test set. The figures of merit were calculated to assess the quality of the model. Sensitivity, specificity, and efficiency rates were, respectively, 98,9%, 98.4% and 98.6%, for the calibration set. For the validation group, the classification accuracy was 100%. Correct classification rates for the internal validation set and external test set were 100% and 79.1% respectively. The technique is clean, fast, relatively low-cost, and non-destructive. Damaged regions of the samples were avoided by using the attached microscope. Limiting the age of the samples to a maximum of 10 years was enough to avoid misclassifications due to the natural degradation and weathering of the sample. Since the external test group is formed by underrepresented classes, its correct classification rate (79.1%) can be potentially improved at any time, by including and analyzing more samples.

Non-Destructive Subsurface Inspection of Marine and Protective Coatings Using Near- and Mid-Infrared Optical Coherence Tomography

Near- and mid-infrared optical coherence tomography (OCT) is evaluated as a non-destructive and non-contact reflection imaging modality for inspection of industrial and marine coatings. Near-infrared OCT was used to obtain high-resolution images (~6/2 µm lateral/axial) of hidden subsurface cracks and defects in a resin base coating, which had been exposed to high pressure and high temperature to study coating degradation in hostile environments. Mid-infrared OCT was employed for high-resolution (~15/8.5 µm lateral/axial) subsurface inspection of highly scattering marine coatings, demonstrating monitoring of wet film thickness and particle dispersion during curing of a 210 µm layer of antifouling coating, and detection of substrate corrosion through 369 µm of high-gloss alkyd enamel. Combining high-resolution and fast, non-invasive scanning, OCT is therefore considered a promising tool for studying coating performance and for industrial inspection.

Sub-surface characterisation of latest-generation identification documents using optical coherence tomography

The identification of individuals, particularly at international border crossings, coupled with the evolving sophistication of identity documents are issues that authorities must contend with. Particularly, the ability to distinguish legitimate from counterfeit documents, with high throughput, sensitivity, and selectivity is an ever-evolving challenge. Over the last decade, an increasing number of security features have been introduced by authorities in identification documents. The latest generation of travel documents (such as passports and national ID cards) forego paper substrates for several layers of polycarbonate, allowing security features to be embedded within the documents. These security features may contain information at either the superficial and sub-surface levels, thus increasing the document's resilience to counterfeiting. As the documents become harder to forge, so does the sophistication of forgery detection. There appears to be an unmet and evolving need to identify such sophisticated forgeries, in a non-destructive, high throughput manner. In this publication, we report on the application of optical coherence tomography (OCT) imaging on assessing security features in specimen passports and national ID cards. OCT allows sub-surface imaging of translucent structures, non-destructively enabling quantitative visualisation of embedded security features.

Initial Study for the Determination of the Sequence of Intersecting Lines between Gel Pens and Seals by Optical Coherence Tomography

Determining the sequence of intersecting lines is a significant issue in the forensic document examination that can reveal the fraud or distinguish between different allegations. Optical coherence tomography (OCT) is a high-resolution cross-sectional imaging technique that has been introduced into forensic science field recently. The potential of OCT as a novel method to determine the sequence of intersecting lines was examined for the first time. In this study, a spectral-domain OCT system with a center wavelength of 900 nm was employed to perform nondestructive examination on determining the sequence of 18 heterogeneous intersecting line samples produced using three types of gel pens and three brands of stamp pad ink seals. Two-dimensional (2D) cross-sectional, and three-dimensional (3D) volumetric images of the intersecting lines were obtained by the OCT system. Several features were noted and analyzed to successfully determine the sequence of all the 18 samples. Blind tests were also conducted to demonstrate the effectiveness of OCT technique. The results illustrate that OCT technology can provide an effective and accurate method for sequencing intersecting lines of gel pen ink and seal ink, which may complement the conventional methods used in the examination of questioned documents.

Non-destructive analysis of flake properties in automotive paints with full-field optical coherence tomography and 3D segmentation

Automotive coating systems are designed to protect vehicle bodies from corrosion and enhance their aesthetic value. The number, size and orientation of small metallic flakes in the base coat of the paint has a significant effect on the appearance of automotive bodies. It is important for quality assurance (QA) to be able to measure the properties of these small flakes, which are approximately 10μm in radius, yet current QA techniques are limited to measuring layer thickness. We design and develop a time-domain (TD) full-field (FF) optical coherence tomography (OCT) system to scan automotive panels volumetrically, non-destructively and without contact. We develop and integrate a segmentation method to automatically distinguish flakes and allow measurement of their properties. We test our integrated system on nine sections of five panels and demonstrate that this integrated approach can characterise small flakes in automotive coating systems in 3D, calculating the number, size and orientation accurately and consistently. This has the potential to significantly impact QA testing in the automotive industry.