Portable multispectral imaging system based on Raspberry Pi

Abstract

Purpose In this work, the authors aim to present a compact low-cost and portable spectral imaging system for general purposes. The developed system provides information that can be used for a fast in situ identification and classification of samples based on the analysis of captured images. The connectivity of the instrument allows a deeper analysis of the images in an external computer. Design/methodology/approach The wavelength selection of the system is carried out by light multiplexing through a light-emitting diode panel where eight wavelengths covering the spectrum from ultraviolet (UV) to near-infrared region (NIR) have been included. The image sensor used is a red green blue – infrared (RGB-IR) micro-camera controlled by a Raspberry Pi board where a basic image processing algorithm has been programmed. It allows the visualization in an integrated display of the reflectance and the histogram of the images at each wavelength, including UV and NIRs. Findings The prototype has been tested by analyzing several samples in a variety of applications such as detection of damaged, over-ripe and sprayed fruit, classification of different type of plastic materials and determination of properties of water. Originality/value The designed system presents some advantages as being non-expensive and portable in comparison to other multispectral imaging systems. The low-cost and size of the camera module connected to the Raspberry Pi provides a compact instrument for general purposes.

Appraisal of Low-Cost Pushbroom Hyper-Spectral Sensor Systems for Material Classification in Reflectance

“…In addition, the need to use MP4 video for the Mk 1 and Mk 2 sensors meant the frames were pre-processed with on-board software, affecting the white balance and gain of the output. This pre-processing has favored the green channel of the camera, de-emphasizing the other bands where red and NIR information are captured [ 26 , 41 ]. Furthermore, it was found that absorption troughs were present in the NIR (700–800 nm) portion of the returned white specular reflection spectrum for the Mk 1 and Mk 2 cameras.…”

“…Tunable liquid crystal or FPI filters were considered, however these were deemed to be too complex for ready manufacture in a STEM context. Previous STEM and open-source research have favored LED-based multispectral; or diffractive-based spectrometer designs [ 11 , 12 , 25 , 26 ], which have taken advantage of readily accessible optical components and may be built using modest manufacturing equipment such as 3D printers, and are sufficiently robust for use in field environments [ 12 ]. Additionally, the design of the sensors only requires electronics to support the imaging sensor, but still requires smooth, continuous movement in order to generate a hyperspectral cube, and therefore requires sequential image capture from the image sensor to build the scene [ 18 ].…”

“…The Raspberry Pi (RPICAM) version 1 and 2 cameras use Bayer filters for color sensing at differing resolutions and frame rates and have been extremely popular and easy to use with science enthusiasts [ 26 , 32 ]. An important consideration of the utility of a particular sensor for a hyperspectral instrument is the presence of a Bayer filter which exists on most color RGB sensors [ 33 ].…”

“…Consideration was given as to the number and types of materials used to characterize the sensors for VIS/NIR utility, particularly in the 600–800 nm (hereafter termed “ferric response”) portion of the spectrum. Color swatches of a known spectral value have been used in previous research to assist in measuring spectral output from sensors, including lander missions flown to Mars since the 1970s [ 15 , 17 , 22 ], multispectral [ 26 ] and hyperspectral applications [ 30 ]. The utility of three cameras for pushbroom sensor designs was trialed with minerals exhibiting phenomenology in the ferric response portion of the spectrum and that have been found in the inner solar system [ 15 , 16 , 45 ].…”

Portable Multispectral System Based on Color Detector for the Analysis of Homogeneous Surfaces

“…In a previous work, the authors presented a compact multispectral system based on a Raspberry Pi module [22]. The low cost and compact size of this camera module, facing other in the market, as well as the processing capacity of the Raspberry in a compact and portable instrument, makes this novel system suitable for a variety of applications.…”