scholarly journals Hyperspectral Imaging for Bloodstain Identification

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3045
Author(s):  
Maheen Zulfiqar ◽  
Muhammad Ahmad ◽  
Ahmed Sohaib ◽  
Manuel Mazzara ◽  
Salvatore Distefano
Keyword(s):  
Hyperspectral Imaging ◽  
Dna Analysis ◽  
Forensic Sciences ◽  
Blood Protein ◽  
Chemical Methods ◽  
Acrylic Paint ◽  
Spectral Bands ◽  
Nail Polish ◽  
Spatial Dimensions ◽  
Non Destructive

Blood is key evidence to reconstruct crime scenes in forensic sciences. Blood identification can help to confirm a suspect, and for that reason, several chemical methods are used to reconstruct the crime scene however, these methods can affect subsequent DNA analysis. Therefore, this study presents a non-destructive method for bloodstain identification using Hyperspectral Imaging (HSI, 397–1000 nm range). The proposed method is based on the visualization of heme-components bands in the 500–700 nm spectral range. For experimental and validation purposes, a total of 225 blood (different donors) and non-blood (protein-based ketchup, rust acrylic paint, red acrylic paint, brown acrylic paint, red nail polish, rust nail polish, fake blood, and red ink) samples (HSI cubes, each cube is of size 1000 × 512 × 224, in which 1000 × 512 are the spatial dimensions and 224 spectral bands) were deposited on three substrates (white cotton fabric, white tile, and PVC wall sheet). The samples are imaged for up to three days to include aging. Savitzky Golay filtering has been used to highlight the subtle bands of all samples, particularly the aged ones. Based on the derivative spectrum, important spectral bands were selected to train five different classifiers (SVM, ANN, KNN, Random Forest, and Decision Tree). The comparative analysis reveals that the proposed method outperformed several state-of-the-art methods.

scholarly journals A Low-Rate Video Approach to Hyperspectral Imaging of Dynamic Scenes

2018 ◽  
Vol 5 (1) ◽  
pp. 6 ◽  
Author(s):  
Charles Bachmann ◽  
Rehman Eon ◽  
Christopher Lapszynski ◽  
Gregory Badura ◽  
Anthony Vodacek ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Hyperspectral Imaging ◽  
Dynamic Range ◽  
Hyperspectral Image ◽  
Image Sequences ◽  
Integrated System ◽  
Imaging Systems ◽  
Spectral Bands ◽  
Spatial Dimensions ◽  
Low Rate

The increased sensitivity of modern hyperspectral line-scanning systems has led to the development of imaging systems that can acquire each line of hyperspectral pixels at very high data rates (in the 200–400 Hz range). These data acquisition rates present an opportunity to acquire full hyperspectral scenes at rapid rates, enabling the use of traditional push-broom imaging systems as low-rate video hyperspectral imaging systems. This paper provides an overview of the design of an integrated system that produces low-rate video hyperspectral image sequences by merging a hyperspectral line scanner, operating in the visible and near infra-red, with a high-speed pan-tilt system and an integrated IMU-GPS that provides system pointing. The integrated unit is operated from atop a telescopic mast, which also allows imaging of the same surface area or objects from multiple view zenith directions, useful for bi-directional reflectance data acquisition and analysis. The telescopic mast platform also enables stereo hyperspectral image acquisition, and therefore, the ability to construct a digital elevation model of the surface. Imaging near the shoreline in a coastal setting, we provide an example of hyperspectral imagery time series acquired during a field experiment in July 2017 with our integrated system, which produced hyperspectral image sequences with 371 spectral bands, spatial dimensions of 1600 × 212, and 16 bits per pixel, every 0.67 s. A second example times series acquired during a rooftop experiment conducted on the Rochester Institute of Technology campus in August 2017 illustrates a second application, moving vehicle imaging, with 371 spectral bands, 16 bit dynamic range, and 1600 × 300 spatial dimensions every second.

scholarly journals The Performances of Hyperspectral Sensors for Proximal Sensing of Nitrogen Levels in Wheat

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4550
Author(s):  
Huajian Liu ◽  
Brooke Bruning ◽  
Trevor Garnett ◽  
Bettina Berger
Keyword(s):  
Hyperspectral Imaging ◽  
High Throughput ◽  
Management Practices ◽  
Leaf Tissue ◽  
Plant Phenotyping ◽  
Proximal Sensing ◽  
N Content ◽  
Hyperspectral Sensors ◽  
Wheat Leaves ◽  
Non Destructive

The accurate and high throughput quantification of nitrogen (N) content in wheat using non-destructive methods is an important step towards identifying wheat lines with high nitrogen use efficiency and informing agronomic management practices. Among various plant phenotyping methods, hyperspectral sensing has shown promise in providing accurate measurements in a fast and non-destructive manner. Past applications have utilised non-imaging instruments, such as spectrometers, while more recent approaches have expanded to hyperspectral cameras operating in different wavelength ranges and at various spectral resolutions. However, despite the success of previous hyperspectral applications, some important research questions regarding hyperspectral sensors with different wavelength centres and bandwidths remain unanswered, limiting wide application of this technology. This study evaluated the capability of hyperspectral imaging and non-imaging sensors to estimate N content in wheat leaves by comparing three hyperspectral cameras and a non-imaging spectrometer. This study answered the following questions: (1) How do hyperspectral sensors with different system setups perform when conducting proximal sensing of N in wheat leaves and what aspects have to be considered for optimal results? (2) What types of photonic detectors are most sensitive to N in wheat leaves? (3) How do the spectral resolutions of different instruments affect N measurement in wheat leaves? (4) What are the key-wavelengths with the highest correlation to N in wheat? Our study demonstrated that hyperspectral imaging systems with satisfactory system setups can be used to conduct proximal sensing of N content in wheat with sufficient accuracy. The proposed approach could reduce the need for chemical analysis of leaf tissue and lead to high-throughput estimation of N in wheat. The methodologies here could also be validated on other plants with different characteristics. The results can provide a reference for users wishing to measure N content at either plant- or leaf-scales using hyperspectral sensors.

Detection of bloodstains using attenuated total reflectance-Fourier transform infrared spectroscopy supported with PCA and PCA–LDA

2021 ◽  
pp. 002580242110109
Author(s):  
Sweety Sharma ◽  
Rito Chophi ◽  
Jaskirandeep Kaur Jossan ◽  
Rajinder Singh
Keyword(s):  
Fourier Transform ◽  
Ftir Spectroscopy ◽  
Body Fluid ◽  
Due Process ◽  
Dna Analysis ◽  
Fourier Transform Infrared ◽  
Body Fluids ◽  
Attenuated Total Reflectance ◽  
Total Reflectance ◽  
Non Destructive

The most important task in a criminal investigation is to detect and identify the recovered biological stains beyond reasonable scientific doubt and preserve the sample for further DNA analysis. In the light of this fact, many presumptive and confirmatory tests are routinely employed in the forensic laboratories to determine the type of body fluid. However, the currently used techniques are specific to one type of body fluid and hence it cannot be utilized to differentiate multiple body fluids. Moreover, these tests consume the samples in due process, and thus it becomes a great limitation especially considering the fact that samples are recovered in minute quantity in forensic cases. Therefore, such limitations necessitate the use of non-destructive techniques that can be applied simultaneously to all types of bodily fluids and allow sample preservation for further analysis. In the current work, attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy has been used to circumvent the aforementioned limitations. The important factors which could influence the detection of blood such as the effect of substrates, washing/chemical treatment, ageing, and dilution limits on the analysis of blood have been analysed. In addition, blood discrimination from non-blood substance (biological and non-biological in nature) has also been studied. Chemometric technique that is PCA–LDA has been used to discriminate blood from other body fluids and it resulted in 100% accurate classification. Furthermore, blood and non-blood substances including fake blood have also been classified into separate clusters with a 100% accuracy, sensitivity, and specificity. All-inclusive, this preliminary study substantiates the potential application of ATR-FTIR spectroscopy for the non-destructive identification of blood traces in simulated forensic casework conditions with 0% rate of false classification.

scholarly journals Forensic analysis of beverage stains using hyperspectral imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Binu Melit Devassy ◽  
Sony George
Keyword(s):  
Hyperspectral Imaging ◽  
Crime Scene ◽  
Forensic Analysis ◽  
Classification Model ◽  
Support Vector ◽  
Additional Information ◽  
Non Invasive ◽  
Spectral Bands ◽  
Data Dimensionality Reduction ◽  
Gradient Based

AbstractDocumentation and analysis of crime scene evidences are of great importance in any forensic investigation. In this paper, we present the potential of hyperspectral imaging (HSI) to detect and analyze the beverage stains on a paper towel. To detect the presence and predict the age of the commonly used drinks in a crime scene, we leveraged the additional information present in the HSI data. We used 12 different beverages and four types of paper hand towel to create the sample stains in the current study. A support vector machine (SVM) is used to achieve the classification, and a convolutional auto-encoder is used to achieve HSI data dimensionality reduction, which helps in easy perception, process, and visualization of the data. The SVM classification model was re-established for a lighter and quicker classification model on the basis of the reduced dimension. We employed volume-gradient-based band selection for the identification of relevant spectral bands in the HSI data. Spectral data recorded at different time intervals up to 72 h is analyzed to trace the spectral changes. The results show the efficacy of the HSI techniques for rapid, non-contact, and non-invasive analysis of beverage stains.

scholarly journals Identification of pigments in artworks by inverse tangent derivative of spectrum and a new filtering method

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
F. Fazlali ◽  
S. Gorji Kandi
Keyword(s):  
Reflectance Spectrum ◽  
Practical Method ◽  
Chemical Methods ◽  
Munk Function ◽  
Absorption Of Light ◽  
Spectrophotometric Data ◽  
First Time ◽  
Non Destructive ◽  
Derivatives Of

Abstract Employing an economical and non-destructive method for identifying pigments utilized in artworks is a significant aspect for preserving their antiquity value. One of the non-destructive methods for this purpose is spectrophotometry, which is based on the selected absorption of light. Mathematical descriptive methods such as derivatives of the reflectance spectrum, the Kubelka–Munk function and logarithm have been employed for the characterization of the peak features corresponding to the spectrophotometric data. In the present study, the mentioned mathematical descriptive methods were investigated with the aim to characterize the constituents of an Iranian artwork but were not efficient for the samples. Therefore, inverse tangent derivative equation was developed on spectral data for the first time, providing considerable details in the profile of reflectance curves. In the next part, to have a simpler and more practical method it was suggested to use filters made up of pure pigments. By using these filters and placing them on the samples, imaging was done. Then, images of samples with and without filter were evaluated and pure pigments were distinguished. The mentioned methods were also used to identify pigments in a modern Iranian painting specimen. The results confirmed these methods with reliable answers indicating that physical methods (alongside chemical methods) can also be effective in determining the types of pigments.

scholarly journals Vis/NIR hyperspectral imaging for detection of hidden bruises on kiwifruits

2011 ◽  
Vol 29 (No. 6) ◽  
pp. 595-602 ◽  
Author(s):  
Q. Lü ◽  
M.-j. Tang ◽  
J.-r. Cai ◽  
J.-w. Zhao ◽  
S. Vittayapadung
Keyword(s):  
Hyperspectral Imaging ◽  
Hyperspectral Image ◽  
Detection System ◽  
Image Data ◽  
Principal Component ◽  
Quality Analysis ◽  
Economic Losses ◽  
Hyperspectral Image Data ◽  
Multispectral Detection ◽  
Non Destructive

It is necessary to develop a non-destructive technique for kiwifruit quality analysis because the machine injury could lower the quality of fruit and incur economic losses. Bruises are not visible externally owing to the special physical properties of kiwifruit peel.We proposed the hyperspectral imaging technique to inspect the hidden bruises on kiwifruit. The Vis/NIR (408–1117 nm) hyperspectral image data was collected. Multiple optimal wavelength (682, 723, 744, 810, and 852 nm) images were obtained using principal component analysis on the high dimension spectral image data (wavelength range from 600 nm to 900 nm). The bruise regions were extracted from the component images of the five waveband images using RBF-SVM classification. The experimental results showed that the error of hidden bruises detection on fruits by means of hyperspectral imaging was 12.5%. It was concluded that the multiple optimal waveband images could be used to constructs a multispectral detection system for hidden bruises on kiwifruits.

scholarly journals INFORMATION EXTRACTION IN TOMB PIT USING HYPERSPECTRAL DATA

2018 ◽  
Vol XLII-3 ◽  
pp. 2107-2111
Author(s):  
X. Yang ◽  
M. Hou ◽  
S. Lyu ◽  
S. Ma ◽  
Z. Gao ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Visual Experience ◽  
Hyperspectral Data ◽  
Shanxi Province ◽  
Bottom Surface ◽  
Archaeological Research ◽  
Reference Images ◽  
Research Findings ◽  
And Storage ◽  
Non Destructive

Hyperspectral data has characteristics of multiple bands and continuous, large amount of data, redundancy, and non-destructive. These characteristics make it possible to use hyperspectral data to study cultural relics. In this paper, the hyperspectral imaging technology is adopted to recognize the bottom images of an ancient tomb located in Shanxi province. There are many black remains on the bottom surface of the tomb, which are suspected to be some meaningful texts or paintings. Firstly, the hyperspectral data is preprocessing to get the reflectance of the region of interesting. For the convenient of compute and storage, the original reflectance value is multiplied by 10000. Secondly, this article uses three methods to extract the symbols at the bottom of the ancient tomb. Finally we tried to use morphology to connect the symbols and gave fifteen reference images. The results show that the extraction of information based on hyperspectral data can obtain a better visual experience, which is beneficial to the study of ancient tombs by researchers, and provides some references for archaeological research findings.

From Optical to Hyperspectral Imaging Techniques in Forensic Sciences

2016 ◽  
pp. 125-149 ◽  
Author(s):  
Maria Ángeles Fernández de la Ossa ◽  
María Lopez-López ◽  
Matías Calcerrada ◽  
Carmen García-Ruiz
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging Techniques ◽  
Forensic Sciences
Sign in / Sign up

Export Citation Format

Share Document