Hyperspectral
imaging (HSI) technology is widely used nowadays for food quality and safety
analysis to handle limitations of conventional methods[1,2]. The conventional
methods are considered time-consuming, laborious, destructive, required complex
sample preparation, required chemical substances, required experts all the
time, and some of them are subjective. Applications of HSI technology give a
huge benefit for food industries through providing a fast, fully automatic,
non-invasive, chemical-free and robust quality and safety assessments. Compared
with computer vision and spectroscopy, HIS produces richer data containing
spatio-spectral information[2]. The spatio-spectral information is formed in
three-dimensional array called a hypercube. A robust acquisition process of
hypercubes is essentially needed since a particular spectral fingerprint of an
object can be extracted from the hypercube[3,4]. One key factor to get accurate
hypercubes is a proper lighting configuration. The lighting becomes very
important for HSI because, like other optical instruments, hyperspectral
imagers measure the energy changing of electromagnetic waves in the form of
light[5]. This project is intended to develop an optimal lighting configuration
for a general purposes food quality and safety analysis based on HSI
technology. The type of light sources and the model of light sources holders
are need to be investigated so that they meet with the requirements of HSI
technology.
This requires designing a proper base to lay out a big array of LEDs with
multitude wavelengths so as to be directed toward the subject under test. A
normal web camera will be used to capture the image of the subject.
References
[1] Wu, D. and Sun, D.-W. (2013), ‘Advanced applications of hyperspectral
imaging technology for food quality and safety analysis and assessment: A
review—part ii: Applications’, Innovative Food Science & Emerging
Technologies 19, 1–14.
[2] Sun, D.-W. (2010), Hyperspectral imaging for food quality analysis and
control, Elsevier.
[3] Lorente, D., Aleixos, N., Gómez-Sanchis, J., Cubero, S., García-Navarrete,
O. L. and Blasco, J. (2012), ‘Recent advances and applications of hyperspectral
imaging for fruit and vegetable quality assessment’, Food and Bioprocess
Technology 5(4), 1121–1142.
[4] Huang, H., Liu, L. and Ngadi, M. O. (2014), ‘Recent developments in
hyperspectral imaging for assessment of food quality and safety’, Sensors
14(4), 7248–7276.
[5] Holler, F. J., Skoog, D. A. and Crouch, S. R. (2007), ‘Principles of
instrumental analysis’, Belmont:Thomson.
Undergraduate
Hardware setup to be used for hyperspectral imaging research
Sound electronic design skills
Lab allocations have not been finalised