- Email: [email protected]
Hyperspectral imaging: Anew prospective for remote recognition of explosive materials
Author’s Accepted Manuscript Hyperspectral Imaging: Anew Prospective for Remote Recognition of Explosive Materials Yasser H. El-Sharkawy, Sherif Elbasuney
www.elsevier.com/locate/rsase
PII: DOI: Reference:
S2352-9385(18)30234-9 https://doi.org/10.1016/j.rsase.2018.10.016 RSASE182
To appear in: Remote Sensing Applications: Society and Environment Received date: 11 July 2018 Revised date: 23 October 2018 Accepted date: 24 October 2018 Cite this article as: Yasser H. El-Sharkawy and Sherif Elbasuney, Hyperspectral Imaging: Anew Prospective for Remote Recognition of Explosive Materials, Remote Sensing Applications: Society and Environment, https://doi.org/10.1016/j.rsase.2018.10.016 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Hyperspectral Imaging: Anew Prospective for Remote Recognition of Explosive Materials Yasser H. El-Sharkawy a, Sherif Elbasuney b1* a
Head of Department of biomedical Engineering, Military Technical Collage, Kobry Elkoba, Cairo, Egypt.
b
Head of Nanotechnology research center, School of Chemical Engineering, Military Technical College,
Kobry El-Kobba, Cairo, Egypt.
[email protected], [email protected],
Abstract The recent development of hyperspectral imaging and pattern recognition can find wide applications in recognition of explosive materials. This study reports on novel technique for remote sensing of explosive material using hyperspectral imaging. Common explosive materials including TNT, RDX, and HMX were illuminated with multi-spectral line sources at 457, 488, and 514 nm with energy 10 mW. Furthermore, mercury lamp was employed to represent the outdoor environment. The reflected and emitted light of each tested explosive material was collected using hyperspectal camera to generate cubic images. The variation of reflected energy as function of wavelength was employed to generate characteristic spectrum of each explosive material. This approach offered standoff imaging of all concealed explosive materials at 569.6, 641.2, and 743 nm. Nitramine explosives (RDX and HMX) were distinguished from TNT at 395.5, and 626.2 nm. HMX was distinguished from RDX at 771 nm. A novel digital signal processing algorithm was employed for TNT recognition through normalization of reflectance spectral images with subsequent subtraction. Where, spectral image in UV band (395.52nm) was subtracted from spectral image in visible band (569.6 nm). This novel approach offered discrimination of TNT from all other explosive materials. Edge detection and noise removal was performed using two-D Hilbert transform. In conclusion, we report on novel, non-invasive, non-contact technique for remote recognition of hidden explosive material.
Keywords: Explosive detection, Forensic analysis, Hyperspectral imaging, Digital signal processing. 1
Tel: +201112630789
1
1. Introduction Terrorism activities caused 25,673 deaths, and global economic loses of US$84 billion in 2016 only [1]. As a result of the continuous threat of terrorism, it is becoming necessary to design new robust analytical techniques for fast identification of explosive materials [2-3]. The main target in forensic science is the development of remote detection technology that should fulfill the following requirements [4-7]:
High sensitivity and selectivity.
Ability for hidden explosive materials identification.
Standoff capabilities to minimize the risk of operators.
Reducing the possibility of sample contamination or destruction.
Portable technology for crime scene operation.
Remote sensing using hyperspectral imaging could fulfill these requirements [8-9]. Hyperspectral imaging is an emergent technology that can find wide applications in many research areas, such as agriculture, mapping, and target detection [10-13]. This technique gives the ability to remotely identify the composition of each pixel of the generated image [14]. Therefore, it is a novel candidate for detection of hidden explosive materials, as a result of its inherent safety and fast response time [15-17]. When explosive material is illuminated with monochromatic light beam of proper wavelength and energy; incident photons can interact with the sample surface [18-19]. Energy can be absorbed, transmitted, scattered, and reflected by that surface [20]. The amount of reflected energy as a function of wavelength can offer information about chemical and physical properties of tested material [21]. The ratio of the reflected energy to the incident energy is termed the reflectance [22]. The reflectivity of the sample is chemical composition dependant. The reflected signal will be affected with the following parameters [23]:
Optical properties of the sample under investigation.
Characteristics of the illumination light source.
Detector sensitivity.
Each material has its own unique characteristic optical properties at the illuminating wavelength; therefore different optical properties impinging light in a wavelength-dependent fashion [24-27].
2
The reflected light, R (λ), can be expressed as the product of the radiance of illuminated area L (λ) and the sample reflectance spectrum ρ(λ ) (Equation 1)[28].
R (λ) = L(λ ) ρ(λ )
(1)
As reflectance is function of wavelength, therefore each explosive material can demonstrate its own characteristic spectral reflectance [7, 29-31]. Consequently an album of cubic image can be generated to distinguish between different explosive materials (Figure 1).
(b)
(a)
Fig. 1: Schematic for: Electromagentic spectrum (a), Cubic image generation through hyperspectral camera (b) [32]. Each explosive material can demonstrate its own characteristic cubic image that can be employed for instant identification and discriminating between different explosives. Furthermore, this cubic image can be employed to develop an electronic data base library [33-37]. This study reports on novel approach for remote sensing of concealed explosive materials including TNT, RDX, and HMX. The tested materials were illuminated with multi-spectral line sources at 457, 488, and 514 nm with energy 10 m watt. Mercury lamp was superimposed to represent the outdoor environment. The collected spectral reflectance by hyperspectral camera was analyzed via customized image processing algorithm in an attempt to extract characteristic information for each explosive material. This approach offered standoff imaging of all concealed explosive materials. A novel digital signal processing algorithm
3
was employed for TNT recognition through normalized spectral image differential and edge detection using two-D Hilbert transform [28].
2. Experimental This study reports on novel approach for remote sensing of explosive materials. The tested materials were illuminated using multi-spectral line sources (457nm, 488nm, and 514nm) of 10 mW power. The illuminating lines were superimposed on commercial mercury lamp spectrum. However, halogen lamp could be the better choice to mimic sunlight; this could be a point of research in the future work. Hyperspectral camera model OCI TM- UAV-1000 with spectral resolution < 5 nm, and an objective lens to adjust the range of light collection, was employed. The employed detector can offer both spectral and spatial information simultaneously to reconstruct and store a three-dimensional hypercube image for each tested material. Three main explosive materials including TNT, RDX, and HMX were concealed in poly ethylene plastic tube. 2 g of each sample was employed for this study (Figure 2). Model OCI TM- UAV-1000 nm
Mercury lamp
RDX
TNT
HMX
Multi spectral line sources
Fig. 2: Schematic for customized hyperspectral imaging system for remote sensing of concealed explosive materials.
4
2.1 Reflectance calibration The purpose of reflectance calibration is to adjust the recorded sample images from the dark current of the camera. The dark effect (D) is the ambient background response of camera caused by dark current of the instrument. The dark response is captured by turning off the illumination light source, completely by covering the lens with its cap or black cover, and acquiring the camera response. The bright response (W) recording the total reflected light intensity from the illumination using white object as a sample and measure the reflected light. After the reflected light response (I) of the sample is measured, the corrected reflectance value (C) is calculated as follows:
2
Where: C, I, W, D are corrected reflectance value, reflectance light response, bright response, dark response.
2.2 Image processing Standard white material was employed for calibration of hyperspectral camera before operation. The recorded hyperspectral image intensity is varied with light reflectance and emittance according to Equation 1. After the signals were calibrated according to Equation 2; an image preprocessing sequences was employed to enhance the signal to noise at different regions of the image [32]. Edge detection technique based on 2D Hilbert transform and noise removal using moving average filter were employed for sample pattern recognition [28]. Novel customized difference spectral imaging analysis algorithm was employed for remote sensing of TNT material. Full representation of main signal processing stages is represented in Figure 3.
5
Reflectance Calibration
Image Processing
Spectral Processing
Qualitative/Quantitative analysis prediction Fig. 3: Flow diagram of explosive recognition using hyperspectral data analysis process.
2.3 Qualitative and quantitative analysis The limitation of hyperspectral imaging technique is that Cubic image (large album of images) can be generated and few of them can provide the desired representative information. To overcome this drawback, 1D spectrum response (Reflectance function in wavelength) was developed in an attempt to explore the difference in reflectance of the tested explosive materials as function of wavelength. Therefore the characteristic wavelengths for each explosive material can be identified. Spectral reflectance at certain wavelength can be employed not only for remote sensing of explosive materials but also to differentiate between explosive materials with similar chemical structure.
3. Results and discussions The reflectance spectral images for tested explosive materials including RDX, HMX, and TNT was transformed to 1 D spectrum using HSAnalysis2XL software associated with the employed hyperspectral camera
in an attempt to retrieve the characteristic absorption/reflection lines for each explosive
6
material. This approach can offer a quick indication of frames that can provide valuable information about chemical structure.
3.1 Spectral data Each explosive material has its own optical properties; consequently it can offer its own characteristics absorption lines. For instance, TNT demonstrated high absorption at 426.24, 538.88, and 569.6 nm, relative to RDX and HMX. This can be ascribed to the weak π bond cloud associated with the aromatic ring [38-39]. The origin of absorption lines can be correlated to electronic transitions of stimulated molecules by incident light. These transitions can offer characteristic spectral signature for each explosive material (Figure 4).
Reflectance spectral signal for background paper
RDX
TNT
HMX
Fig. 4: Reflectance spectral signals for tested explosive materials including: TNT, RDX, and HMX. The difference in central wavelength and full width can offer further discrimination between similar spectral signatures. Whereas RDX and HMX have similar chemical structure that could be difficult to discriminate using different spectroscopic techniques; reflectance spectral imaging demonstrated characteristic spectrum lines for each material. In an attempt to achieve good discrimination between similar explosive materials; the difference in reflectance spectral signal should be maximized. This has
7
been accomplished using logarithmic scale using non linear filter (Figure 5). Further details about nonlinear filter (logarithmic scale) for image enhancement can be found in the following references [40-42]
Background
TNT RDX HMX
Fig. 5: Log scale differential reflectance spectrum of some common explosive materials (RDX, TNT, and HMX).
Figure 5 demonstrated that there is a good chance to discriminate between two similar explosive material RDX and HMX at 771 nm; where RDX demonstrated high reflectance relative to HMX.
3.2 Image sets The cubic image can be divided into three main image sets according to the illumination conditions as well as received signal band. Each tested material was illuminated with light sources that cover the main three bands (ultra-violet, visible, and infrared). The employed light sources include: UV illumination using mercury lamp, this light source can produce reflectance at the same incident wavelengths and emission at higher wave lengths. Visible illumination using multispectral line sources and mercury lamp, this light source can offer reflectance and emission in visible and IR. Infrared illumination mercury lamp to produced infrared-reflected images only.
8
The generated reflected spectral image and corresponding image sets related to illuminating source can be represented in Figure 6 [32].
Fig. 6: Reconstructed cubic image represented by number of image sets according to illumination conditions and reflected/emitted radiation, Key: reflected spectral at UV (UVR), illumination at UV (UVL), reflected spectral at VIS, illumination at VIS (VIL(short), VIVL(long), reflected spectral at IR (IIR)[28].
3.3 Reflectance spectral images For reflectance spectral images, the wavelength range of the reflected radiation will be the same as the illuminating radiation. The intensity of reflected radiation will be a function of the optical properties of the tested explosive material. Therefore it can provide distinguished characteristics of each explosive material. The first reflected set over the visible band (400-700 nm) were recorded for the investigated sample after being illuminated. The collected images were processed for noise removal and enhanced signal to noise ratio as reported in section 2.2. It was possible to construct reflectance spectral image for all three hidden explosive materials at 569 and 641 nm (windows 5, 6 - Figure 6). While TNT did not demonstrate spectral reflectance image at 426 and 477, and 538; RDX and HMX demonstrated high quality images at these wavelengths (windows 2, 3, 4 - Figure 6).
9
The second set is infrared-reflected (IRR) images recorded over the infrared region (700-1100 nm), as the tested sample was illuminated with infrared radiation. The recorded images represent valuable information in revealing different hidden explosive materials. While all three explosive materials were detected at 743 nm (window 7 - Figure 6); HMX demonstrated characteristic image at 771 nm (window 8 - Figure 6). Consequently 771 nm could be the unique wavelength (fingerprint signature) for HMX imaging. The third set is ultraviolet region (200-400 nm) reflected from the investigated sample when it was under illumination with UV radiation. While TNT did not show any reflectance over this region; RDX and HMX demonstrated high quality spectral reflectance image at 395 nm (Window 1 – Figure 6).
Windows 9 – Figure 6 demonstrates the contour images for investigated three explosive materials using DSB 6 algorithm over the three illuminating bands. This was conducted in an attempt to demonstrate the relative intensity of reflected spectral image as a function of wavelength.
10
Window 1
Window 2
Window 3
Window 4
Window 5
Window 6
Window 7
Window 8
Window 9
UV
Vis
IR
Fig. 6: Represent custom worksheet for the ultraviolet, visible and infrared spectrum as related to the wavelength resolved bands corresponding to a spectral image of explosive materials (RDX, TNT, and HMX) It can be concluded that all three types of explosive materials demonstrated high spectral reflectance over the visible band as these materials do not have high absorbance over the visible region. The energy of light over the visible region is not enough to excite the valence electrons [43-45]. On the other hand TNT did not demonstrate high spectral reflectance image over UV region as it has high absorption due to excitation of weak π bonds of the benzene aromatic ring [46]. RDX and HMX demonstrated high spectral reflectance over UV region as they have low UV absorption due to their saturated structure (single bonds)[39, 47].
11
HMX demonstrated high reflectance over IR region compared with TNT and RDX. This was correlated to the high reactivity of TNT and RDX over IR region with high absorption due molecular vibration relative to HMX which could be IR inactive. Figure 7 demonstrated the reflectance spectral imaging for investigated explosive materials over three imaging sets (UV - Vis – IR) as well as the color contour map for relative spectral reflectance intensity.
(a)
(i)
UV image set
(b)
(i)
UV image set
(ii)
Vis image set
(ii)
Vis image set
(iii)
IR image set
(iii)
IR image set
Fig. 7: The ultraviolet, visible and infrared spectrum as related to the wavelength resolved bands corresponding to a spectral image of explosive materials (RDX, TNT, and HMX) (a) gray scale density images, (b) color contour map images.
12
3.4 Subtraction algorithm for TNT discrimination TNT is the most common explosive material in use due to its ease of manufacture from commercial starting materials. TNT is the most encountered material in many terrorist activities [48]. The instant recognition of TNT is vital issue [3, 49]. It was not possible to generate characteristic reflectance spectral image for TNT to discriminate TNT from other explosive materials. TNT demonstrated strong absorption in UV radiation due to its chemical structure which is characterized with high delocalized weakly bonded aromatic electronic cloud. Consequently TNT demonstrated low reflectance spectral image as reported in Figure 7-a-i. In contrast RDX and HMX demonstrated high reflectance spectral image in UV band Figure 7a-i. All three explosive materials demonstrated high reflectance spectral images in far vis band as demonstrated in Figure 7-a-ii. Normalization for spectral reflectance images in Vis and UV bands was performed to compensate visible, UV, and IR-reflected images for the spatial in homogeneities and to establish uniform illumination conditions by normalized spectral reflectance images (Figure 8).
Fig. 8: The mathematical operation of compensating visible, UV- and IR-reflected images for the spatial inhomogeneities of the radiation source and establishing uniform illumination conditions by normalized spectral reflectance images.
13
Normalized images were subjected to spectral subtraction; where spectral image in UV band (395.52nm) subtracted from spectral image in Vis band (569.6 nm). This novel approach offered discrimination of TNT from all other explosive materials (Figure 9-a). For enhanced spectral image (noise removal) edge detection using 2d Hilbert transform was employed (Figure 9-b).
(a)
(b)
Fig. 9: The custom subtraction algorithm developed in order to detect and discriminate TNT explosive materials. The subtraction image exhibited the highest value of TNT intensity. This approach can offer instant identification and recognition of hidden explosive materials even when mixed with other substances, as a result of reflectance spectral image subtraction with 2d Hilbert transform.
Conclusion This study demonstrated the utility of hyperspectral imaging as a novel technology for remote sensing of hidden explosive materials. Remote recognition of common hidden explosive materials i.e. TNT, RDX, HMX was conducted using hyperspectral camera. Reconstructed reflectance spectral images were employed to retrieve characteristic signature for remote recognition of each explosive materials. This approach offered standoff imaging of all concealed explosive materials in visible band at 569.6, 641.2, and 743 nm. Nitramine explosives (RDX and HMX) were distinguished from TNT; as they demonstrated high
14
quality reflectance spectral images at 395.5, and 626.2 nm. HMX was distinguished from RDX at 771 nm. A novel digital signal processing algorithm was employed for TNT recognition through normalization and spectral subtraction of reflectance spectral images with edge detection using two-D Hilbert transform. In conclusion, this study offered non-invasive, non-contact technique for remote recognition of explosive material. This approach can eliminate handling and manipulation of explosive material.
Acknowledgement Military Technical College is acknowledged for funding the research project "New prospective for explosive material detection". This work has been conducted at Nanotechnology research center in collaboration with Department of biomedical Engineering.
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17
www.elsevier.com/locate/rsase
PII: DOI: Reference:
S2352-9385(18)30234-9 https://doi.org/10.1016/j.rsase.2018.10.016 RSASE182
To appear in: Remote Sensing Applications: Society and Environment Received date: 11 July 2018 Revised date: 23 October 2018 Accepted date: 24 October 2018 Cite this article as: Yasser H. El-Sharkawy and Sherif Elbasuney, Hyperspectral Imaging: Anew Prospective for Remote Recognition of Explosive Materials, Remote Sensing Applications: Society and Environment, https://doi.org/10.1016/j.rsase.2018.10.016 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Hyperspectral Imaging: Anew Prospective for Remote Recognition of Explosive Materials Yasser H. El-Sharkawy a, Sherif Elbasuney b1* a
Head of Department of biomedical Engineering, Military Technical Collage, Kobry Elkoba, Cairo, Egypt.
b
Head of Nanotechnology research center, School of Chemical Engineering, Military Technical College,
Kobry El-Kobba, Cairo, Egypt.
[email protected], [email protected],
Abstract The recent development of hyperspectral imaging and pattern recognition can find wide applications in recognition of explosive materials. This study reports on novel technique for remote sensing of explosive material using hyperspectral imaging. Common explosive materials including TNT, RDX, and HMX were illuminated with multi-spectral line sources at 457, 488, and 514 nm with energy 10 mW. Furthermore, mercury lamp was employed to represent the outdoor environment. The reflected and emitted light of each tested explosive material was collected using hyperspectal camera to generate cubic images. The variation of reflected energy as function of wavelength was employed to generate characteristic spectrum of each explosive material. This approach offered standoff imaging of all concealed explosive materials at 569.6, 641.2, and 743 nm. Nitramine explosives (RDX and HMX) were distinguished from TNT at 395.5, and 626.2 nm. HMX was distinguished from RDX at 771 nm. A novel digital signal processing algorithm was employed for TNT recognition through normalization of reflectance spectral images with subsequent subtraction. Where, spectral image in UV band (395.52nm) was subtracted from spectral image in visible band (569.6 nm). This novel approach offered discrimination of TNT from all other explosive materials. Edge detection and noise removal was performed using two-D Hilbert transform. In conclusion, we report on novel, non-invasive, non-contact technique for remote recognition of hidden explosive material.
Keywords: Explosive detection, Forensic analysis, Hyperspectral imaging, Digital signal processing. 1
Tel: +201112630789
1
1. Introduction Terrorism activities caused 25,673 deaths, and global economic loses of US$84 billion in 2016 only [1]. As a result of the continuous threat of terrorism, it is becoming necessary to design new robust analytical techniques for fast identification of explosive materials [2-3]. The main target in forensic science is the development of remote detection technology that should fulfill the following requirements [4-7]:
High sensitivity and selectivity.
Ability for hidden explosive materials identification.
Standoff capabilities to minimize the risk of operators.
Reducing the possibility of sample contamination or destruction.
Portable technology for crime scene operation.
Remote sensing using hyperspectral imaging could fulfill these requirements [8-9]. Hyperspectral imaging is an emergent technology that can find wide applications in many research areas, such as agriculture, mapping, and target detection [10-13]. This technique gives the ability to remotely identify the composition of each pixel of the generated image [14]. Therefore, it is a novel candidate for detection of hidden explosive materials, as a result of its inherent safety and fast response time [15-17]. When explosive material is illuminated with monochromatic light beam of proper wavelength and energy; incident photons can interact with the sample surface [18-19]. Energy can be absorbed, transmitted, scattered, and reflected by that surface [20]. The amount of reflected energy as a function of wavelength can offer information about chemical and physical properties of tested material [21]. The ratio of the reflected energy to the incident energy is termed the reflectance [22]. The reflectivity of the sample is chemical composition dependant. The reflected signal will be affected with the following parameters [23]:
Optical properties of the sample under investigation.
Characteristics of the illumination light source.
Detector sensitivity.
Each material has its own unique characteristic optical properties at the illuminating wavelength; therefore different optical properties impinging light in a wavelength-dependent fashion [24-27].
2
The reflected light, R (λ), can be expressed as the product of the radiance of illuminated area L (λ) and the sample reflectance spectrum ρ(λ ) (Equation 1)[28].
R (λ) = L(λ ) ρ(λ )
(1)
As reflectance is function of wavelength, therefore each explosive material can demonstrate its own characteristic spectral reflectance [7, 29-31]. Consequently an album of cubic image can be generated to distinguish between different explosive materials (Figure 1).
(b)
(a)
Fig. 1: Schematic for: Electromagentic spectrum (a), Cubic image generation through hyperspectral camera (b) [32]. Each explosive material can demonstrate its own characteristic cubic image that can be employed for instant identification and discriminating between different explosives. Furthermore, this cubic image can be employed to develop an electronic data base library [33-37]. This study reports on novel approach for remote sensing of concealed explosive materials including TNT, RDX, and HMX. The tested materials were illuminated with multi-spectral line sources at 457, 488, and 514 nm with energy 10 m watt. Mercury lamp was superimposed to represent the outdoor environment. The collected spectral reflectance by hyperspectral camera was analyzed via customized image processing algorithm in an attempt to extract characteristic information for each explosive material. This approach offered standoff imaging of all concealed explosive materials. A novel digital signal processing algorithm
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was employed for TNT recognition through normalized spectral image differential and edge detection using two-D Hilbert transform [28].
2. Experimental This study reports on novel approach for remote sensing of explosive materials. The tested materials were illuminated using multi-spectral line sources (457nm, 488nm, and 514nm) of 10 mW power. The illuminating lines were superimposed on commercial mercury lamp spectrum. However, halogen lamp could be the better choice to mimic sunlight; this could be a point of research in the future work. Hyperspectral camera model OCI TM- UAV-1000 with spectral resolution < 5 nm, and an objective lens to adjust the range of light collection, was employed. The employed detector can offer both spectral and spatial information simultaneously to reconstruct and store a three-dimensional hypercube image for each tested material. Three main explosive materials including TNT, RDX, and HMX were concealed in poly ethylene plastic tube. 2 g of each sample was employed for this study (Figure 2). Model OCI TM- UAV-1000 nm
Mercury lamp
RDX
TNT
HMX
Multi spectral line sources
Fig. 2: Schematic for customized hyperspectral imaging system for remote sensing of concealed explosive materials.
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2.1 Reflectance calibration The purpose of reflectance calibration is to adjust the recorded sample images from the dark current of the camera. The dark effect (D) is the ambient background response of camera caused by dark current of the instrument. The dark response is captured by turning off the illumination light source, completely by covering the lens with its cap or black cover, and acquiring the camera response. The bright response (W) recording the total reflected light intensity from the illumination using white object as a sample and measure the reflected light. After the reflected light response (I) of the sample is measured, the corrected reflectance value (C) is calculated as follows:
2
Where: C, I, W, D are corrected reflectance value, reflectance light response, bright response, dark response.
2.2 Image processing Standard white material was employed for calibration of hyperspectral camera before operation. The recorded hyperspectral image intensity is varied with light reflectance and emittance according to Equation 1. After the signals were calibrated according to Equation 2; an image preprocessing sequences was employed to enhance the signal to noise at different regions of the image [32]. Edge detection technique based on 2D Hilbert transform and noise removal using moving average filter were employed for sample pattern recognition [28]. Novel customized difference spectral imaging analysis algorithm was employed for remote sensing of TNT material. Full representation of main signal processing stages is represented in Figure 3.
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Reflectance Calibration
Image Processing
Spectral Processing
Qualitative/Quantitative analysis prediction Fig. 3: Flow diagram of explosive recognition using hyperspectral data analysis process.
2.3 Qualitative and quantitative analysis The limitation of hyperspectral imaging technique is that Cubic image (large album of images) can be generated and few of them can provide the desired representative information. To overcome this drawback, 1D spectrum response (Reflectance function in wavelength) was developed in an attempt to explore the difference in reflectance of the tested explosive materials as function of wavelength. Therefore the characteristic wavelengths for each explosive material can be identified. Spectral reflectance at certain wavelength can be employed not only for remote sensing of explosive materials but also to differentiate between explosive materials with similar chemical structure.
3. Results and discussions The reflectance spectral images for tested explosive materials including RDX, HMX, and TNT was transformed to 1 D spectrum using HSAnalysis2XL software associated with the employed hyperspectral camera
in an attempt to retrieve the characteristic absorption/reflection lines for each explosive
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material. This approach can offer a quick indication of frames that can provide valuable information about chemical structure.
3.1 Spectral data Each explosive material has its own optical properties; consequently it can offer its own characteristics absorption lines. For instance, TNT demonstrated high absorption at 426.24, 538.88, and 569.6 nm, relative to RDX and HMX. This can be ascribed to the weak π bond cloud associated with the aromatic ring [38-39]. The origin of absorption lines can be correlated to electronic transitions of stimulated molecules by incident light. These transitions can offer characteristic spectral signature for each explosive material (Figure 4).
Reflectance spectral signal for background paper
RDX
TNT
HMX
Fig. 4: Reflectance spectral signals for tested explosive materials including: TNT, RDX, and HMX. The difference in central wavelength and full width can offer further discrimination between similar spectral signatures. Whereas RDX and HMX have similar chemical structure that could be difficult to discriminate using different spectroscopic techniques; reflectance spectral imaging demonstrated characteristic spectrum lines for each material. In an attempt to achieve good discrimination between similar explosive materials; the difference in reflectance spectral signal should be maximized. This has
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been accomplished using logarithmic scale using non linear filter (Figure 5). Further details about nonlinear filter (logarithmic scale) for image enhancement can be found in the following references [40-42]
Background
TNT RDX HMX
Fig. 5: Log scale differential reflectance spectrum of some common explosive materials (RDX, TNT, and HMX).
Figure 5 demonstrated that there is a good chance to discriminate between two similar explosive material RDX and HMX at 771 nm; where RDX demonstrated high reflectance relative to HMX.
3.2 Image sets The cubic image can be divided into three main image sets according to the illumination conditions as well as received signal band. Each tested material was illuminated with light sources that cover the main three bands (ultra-violet, visible, and infrared). The employed light sources include: UV illumination using mercury lamp, this light source can produce reflectance at the same incident wavelengths and emission at higher wave lengths. Visible illumination using multispectral line sources and mercury lamp, this light source can offer reflectance and emission in visible and IR. Infrared illumination mercury lamp to produced infrared-reflected images only.
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The generated reflected spectral image and corresponding image sets related to illuminating source can be represented in Figure 6 [32].
Fig. 6: Reconstructed cubic image represented by number of image sets according to illumination conditions and reflected/emitted radiation, Key: reflected spectral at UV (UVR), illumination at UV (UVL), reflected spectral at VIS, illumination at VIS (VIL(short), VIVL(long), reflected spectral at IR (IIR)[28].
3.3 Reflectance spectral images For reflectance spectral images, the wavelength range of the reflected radiation will be the same as the illuminating radiation. The intensity of reflected radiation will be a function of the optical properties of the tested explosive material. Therefore it can provide distinguished characteristics of each explosive material. The first reflected set over the visible band (400-700 nm) were recorded for the investigated sample after being illuminated. The collected images were processed for noise removal and enhanced signal to noise ratio as reported in section 2.2. It was possible to construct reflectance spectral image for all three hidden explosive materials at 569 and 641 nm (windows 5, 6 - Figure 6). While TNT did not demonstrate spectral reflectance image at 426 and 477, and 538; RDX and HMX demonstrated high quality images at these wavelengths (windows 2, 3, 4 - Figure 6).
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The second set is infrared-reflected (IRR) images recorded over the infrared region (700-1100 nm), as the tested sample was illuminated with infrared radiation. The recorded images represent valuable information in revealing different hidden explosive materials. While all three explosive materials were detected at 743 nm (window 7 - Figure 6); HMX demonstrated characteristic image at 771 nm (window 8 - Figure 6). Consequently 771 nm could be the unique wavelength (fingerprint signature) for HMX imaging. The third set is ultraviolet region (200-400 nm) reflected from the investigated sample when it was under illumination with UV radiation. While TNT did not show any reflectance over this region; RDX and HMX demonstrated high quality spectral reflectance image at 395 nm (Window 1 – Figure 6).
Windows 9 – Figure 6 demonstrates the contour images for investigated three explosive materials using DSB 6 algorithm over the three illuminating bands. This was conducted in an attempt to demonstrate the relative intensity of reflected spectral image as a function of wavelength.
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Window 1
Window 2
Window 3
Window 4
Window 5
Window 6
Window 7
Window 8
Window 9
UV
Vis
IR
Fig. 6: Represent custom worksheet for the ultraviolet, visible and infrared spectrum as related to the wavelength resolved bands corresponding to a spectral image of explosive materials (RDX, TNT, and HMX) It can be concluded that all three types of explosive materials demonstrated high spectral reflectance over the visible band as these materials do not have high absorbance over the visible region. The energy of light over the visible region is not enough to excite the valence electrons [43-45]. On the other hand TNT did not demonstrate high spectral reflectance image over UV region as it has high absorption due to excitation of weak π bonds of the benzene aromatic ring [46]. RDX and HMX demonstrated high spectral reflectance over UV region as they have low UV absorption due to their saturated structure (single bonds)[39, 47].
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HMX demonstrated high reflectance over IR region compared with TNT and RDX. This was correlated to the high reactivity of TNT and RDX over IR region with high absorption due molecular vibration relative to HMX which could be IR inactive. Figure 7 demonstrated the reflectance spectral imaging for investigated explosive materials over three imaging sets (UV - Vis – IR) as well as the color contour map for relative spectral reflectance intensity.
(a)
(i)
UV image set
(b)
(i)
UV image set
(ii)
Vis image set
(ii)
Vis image set
(iii)
IR image set
(iii)
IR image set
Fig. 7: The ultraviolet, visible and infrared spectrum as related to the wavelength resolved bands corresponding to a spectral image of explosive materials (RDX, TNT, and HMX) (a) gray scale density images, (b) color contour map images.
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3.4 Subtraction algorithm for TNT discrimination TNT is the most common explosive material in use due to its ease of manufacture from commercial starting materials. TNT is the most encountered material in many terrorist activities [48]. The instant recognition of TNT is vital issue [3, 49]. It was not possible to generate characteristic reflectance spectral image for TNT to discriminate TNT from other explosive materials. TNT demonstrated strong absorption in UV radiation due to its chemical structure which is characterized with high delocalized weakly bonded aromatic electronic cloud. Consequently TNT demonstrated low reflectance spectral image as reported in Figure 7-a-i. In contrast RDX and HMX demonstrated high reflectance spectral image in UV band Figure 7a-i. All three explosive materials demonstrated high reflectance spectral images in far vis band as demonstrated in Figure 7-a-ii. Normalization for spectral reflectance images in Vis and UV bands was performed to compensate visible, UV, and IR-reflected images for the spatial in homogeneities and to establish uniform illumination conditions by normalized spectral reflectance images (Figure 8).
Fig. 8: The mathematical operation of compensating visible, UV- and IR-reflected images for the spatial inhomogeneities of the radiation source and establishing uniform illumination conditions by normalized spectral reflectance images.
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Normalized images were subjected to spectral subtraction; where spectral image in UV band (395.52nm) subtracted from spectral image in Vis band (569.6 nm). This novel approach offered discrimination of TNT from all other explosive materials (Figure 9-a). For enhanced spectral image (noise removal) edge detection using 2d Hilbert transform was employed (Figure 9-b).
(a)
(b)
Fig. 9: The custom subtraction algorithm developed in order to detect and discriminate TNT explosive materials. The subtraction image exhibited the highest value of TNT intensity. This approach can offer instant identification and recognition of hidden explosive materials even when mixed with other substances, as a result of reflectance spectral image subtraction with 2d Hilbert transform.
Conclusion This study demonstrated the utility of hyperspectral imaging as a novel technology for remote sensing of hidden explosive materials. Remote recognition of common hidden explosive materials i.e. TNT, RDX, HMX was conducted using hyperspectral camera. Reconstructed reflectance spectral images were employed to retrieve characteristic signature for remote recognition of each explosive materials. This approach offered standoff imaging of all concealed explosive materials in visible band at 569.6, 641.2, and 743 nm. Nitramine explosives (RDX and HMX) were distinguished from TNT; as they demonstrated high
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quality reflectance spectral images at 395.5, and 626.2 nm. HMX was distinguished from RDX at 771 nm. A novel digital signal processing algorithm was employed for TNT recognition through normalization and spectral subtraction of reflectance spectral images with edge detection using two-D Hilbert transform. In conclusion, this study offered non-invasive, non-contact technique for remote recognition of explosive material. This approach can eliminate handling and manipulation of explosive material.
Acknowledgement Military Technical College is acknowledged for funding the research project "New prospective for explosive material detection". This work has been conducted at Nanotechnology research center in collaboration with Department of biomedical Engineering.
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