Hyperspectral Imaging Techniques: an Attractive Solution for the Analysis of Biological and Agricultural Materials

2007 ◽  
pp. 289-311 ◽  
Author(s):  
Vincent Baeten ◽  
Juan Antonio Fernndez Pierna ◽  
Pierre Dardenne
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging Techniques ◽  
Agricultural Materials

scholarly journals Rapid Foreign Object Detection System on Seaweed Using VNIR Hyperspectral Imaging

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5279
Author(s):  
Dong-Hoon Kwak ◽  
Guk-Jin Son ◽  
Mi-Kyung Park ◽  
Young-Duk Kim
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Hyperspectral Imaging ◽  
High Speed ◽  
Detection System ◽  
Imaging Techniques ◽  
Foreign Object ◽  
Subtraction Method ◽  
Foreign Objects ◽  
Time Operation

The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed.

scholarly journals Supervised Machine Learning Methods and Hyperspectral Imaging Techniques Jointly Applied for Brain Cancer Classification

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3827
Author(s):  
Gemma Urbanos ◽  
Alberto Martín ◽  
Guillermo Vázquez ◽  
Marta Villanueva ◽  
Manuel Villa ◽  
...  
Keyword(s):  
Machine Learning ◽  
Blood Vessel ◽  
Hyperspectral Imaging ◽  
Imaging Techniques ◽  
Venous Blood ◽  
Healthy Tissue ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Arterial Blood

Hyperspectral imaging techniques (HSI) do not require contact with patients and are non-ionizing as well as non-invasive. As a consequence, they have been extensively applied in the medical field. HSI is being combined with machine learning (ML) processes to obtain models to assist in diagnosis. In particular, the combination of these techniques has proven to be a reliable aid in the differentiation of healthy and tumor tissue during brain tumor surgery. ML algorithms such as support vector machine (SVM), random forest (RF) and convolutional neural networks (CNN) are used to make predictions and provide in-vivo visualizations that may assist neurosurgeons in being more precise, hence reducing damages to healthy tissue. In this work, thirteen in-vivo hyperspectral images from twelve different patients with high-grade gliomas (grade III and IV) have been selected to train SVM, RF and CNN classifiers. Five different classes have been defined during the experiments: healthy tissue, tumor, venous blood vessel, arterial blood vessel and dura mater. Overall accuracy (OACC) results vary from 60% to 95% depending on the training conditions. Finally, as far as the contribution of each band to the OACC is concerned, the results obtained in this work are 3.81 times greater than those reported in the literature.

Investigation of reflectance, fluorescence, and Raman hyperspectral imaging techniques for rapid detection of aflatoxins in ground maize

Food Control ◽  
2021 ◽  
pp. 108479
Author(s):  
Yong-Kyoung Kim ◽  
Insuck Baek ◽  
Kyung-Min Lee ◽  
Jianwei Qin ◽  
Geonwoo Kim ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Rapid Detection ◽  
Imaging Techniques

The potential of spectral and hyperspectral-imaging techniques for bacterial detection in food: A case study on lactic acid bacteria

Talanta ◽  
2016 ◽  
Vol 153 ◽  
pp. 111-119 ◽  
Author(s):  
Giorgia Foca ◽  
Carlotta Ferrari ◽  
Alessandro Ulrici ◽  
Giorgia Sciutto ◽  
Silvia Prati ◽  
...  
Keyword(s):  
Lactic Acid ◽  
Lactic Acid Bacteria ◽  
Hyperspectral Imaging ◽  
Imaging Techniques ◽  
Bacterial Detection

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

Comparison of hyperspectral imaging techniques for the elucidation of falsified medicines composition

Talanta ◽  
2019 ◽  
Vol 198 ◽  
pp. 457-463 ◽  
Author(s):  
Laureen Coic ◽  
Pierre-Yves Sacré ◽  
Amandine Dispas ◽  
Abdoul Karim Sakira ◽  
Marianne Fillet ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Imaging Techniques ◽  
Falsified Medicines

Hyperspectral imaging techniques for the characterization of Haematococcus pluvialis (Chlorophyceae)

2014 ◽  
Vol 50 (5) ◽  
pp. 939-947 ◽  
Author(s):  
Satoru Nogami ◽  
Shinsuke Ohnuki ◽  
Yoshikazu Ohya
Keyword(s):  
Hyperspectral Imaging ◽  
Haematococcus Pluvialis ◽  
Imaging Techniques
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