Sugar “Imaging” of Fruit Using a Low Cost Charge-Coupled Device Camera

Long, Robert L.; Walsh, Kerry B.; Greensill, Colin Victor.

doi:10.1255/jnirs.536

Cited by 20 publications

(10 citation statements)

References 9 publications

(21 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One of the few studies performed in transmission was the detection of pits in tart cherries [56]. Quantitative investigations encompassed total soluble solids in mango [53], strawberry [54], apple [44], melon (transmission) [57], and kiwi [58]. The paper reporting the determination of total soluble solids in kiwi is probably the first paper being published on the application of NHI in food.…”

Section: Fruit and Vegetablesmentioning

confidence: 99%

Near‐Infrared Hyperspectral Imaging in Food Research

Geladi

Manley

2010

Raman, Infrared, and Near‐Infrared Chemical Imaging

View full text Add to dashboard Cite

It has been known for a very long time that food products can be studied by mid-infrared (MIR) (ca. 2500-15,000 nm) and near-infrared (NIR) (780-2500 nm) spectroscopy, as they contain the C-H, O-H, and N-H bonds that have high absor-banceintheNIRandMIRwavelengthregions.Thesebondsare present in the major constituents of all biological materials. Already during the 1960s and 1970s the pioneers of NIR spectroscopy were mainly interested in food applications, for example, soybeans [1], meat [2], oilseeds [3], and cereals [3][4][5][6][7]. It was found very early that water, fat, protein, and different carbohydrates could be quantified by NIR calibrationsforawidevariety ofagriculturalproducts,half-fabricates, and finished consumer products as presented by various authors [8][9][10][11][12]. Later, constituents such as inorganic salts [13], alcohol [14], fatty acids [15], antioxidants [16,17], and phenolic compounds [17,18] were also quantified, as were physical parameters such as kernel hardness [19][20][21][22][23], maturity [24], and sensory quality [24][25][26]. These analyses are usually done on bulk materials, from which a single NIR spectrum is obtained, as the goal is to integrate over an area that is as large as possible in order to avoid sampling errors. Most food products are inhomogeneous by nature, thus requiring integration or homogenization before bulk NIR measurements. NIR Hyperspectral ImagingThe earliest scientific imaging applications were simple black and white or color images in the visual spectroscopic range, but inspired by satellite imaging, multivariate image analysis [27] was soon becoming useful in the laboratory. Already the first satellite images included wavelengths in the NIR, in addition to visual and MIR wavelengths. Nowadays, hyperspectral imaging [28] is becoming more commonly available, providing complete spectra extending into the long-wave NIR (1100-2500 nm) for each pixel in an image (refer to Chapter 2). The simplest of these images have x and y spatial coordinates and a wavelength coordinate lambda, making a three-way array called a hypercube. This hyperspectral image or hypercube thus allows the description of differences and gradients in the sample under study. Because of this, the samples can be heterogeneous. The spectra in these hyperspectral images show localized spectral features that can be used for exploration and classification. With external information (reference data) also localized, quantitative and qualitative calibrations and predictions are feasible. NIR hyperspectral imaging (NHI) also means that sample preparation different from bulk NIR spectroscopy is needed. Grinding and other homogenization methods are useful for bulk NIR spectroscopic analysis, whereas sampling and sample preparation for NIR imaging have their own peculiarities.Raman, Infrared, and Near-Infrared Chemical Imaging Edited by Slobodan Š ašić and Yukihiro Ozaki

show abstract

Section: Fruit and Vegetablesmentioning

confidence: 99%

Near‐Infrared Hyperspectral Imaging in Food Research

Geladi

Manley

2010

Raman, Infrared, and Near‐Infrared Chemical Imaging

View full text Add to dashboard Cite

show abstract

“…SI has a multitude of applications in many fields (Brady, 2009), including biology (Garini et al, 2006), medicine (Uhr et al, 2012), food inspection (Long et al, 2005), archaeology, art conservation (Lang, 2012), astronomy and remote sensing (Foster et al, 2006). SI with mosaic spectral filter arrays on the image sensor (Themelis et al, 2008) leads to substantial light gathering losses.…”

Section: Introductionmentioning

confidence: 99%

“…SI with mosaic spectral filter arrays on the image sensor (Themelis et al, 2008) leads to substantial light gathering losses. In "staring" or "pushbroom" SI systems (Carlsohn, 2006), removable sets of narrow bandpass filters (Long et al, 2005) or time-sequential dynamic spectral filters (López-Álvarez et al, 2008) slow the SI process and cannot apply it to dynamic, fast changing objects. Modern trends in digital imaging (Brady, 2009) resort to a generic combination of optics with digital processing and to compressed sensing (CS) (Donoho, 2006, Candès et al, 2006 for various purposes and applications.…”

Section: Introductionmentioning

confidence: 99%

Snapshot Spectral and Color Imaging Using a Regular Digital Camera With a Monochromatic Image Sensor

Hauser

Zheludev

Golub

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Commission III, WG III/4KEY WORDS: Multispectral and hyperspectral imaging, Imaging systems, Computational Imaging. ABSTRACT:"Spectral imaging" (SI) refers to the acquisition of the three-dimensional (3D) spectral cube of spatial and spectral data of a source object at a limited number of wavelengths in a given wavelength range. "Snapshot spectral imaging" (SSI) refers to the instantaneous acquisition (in a single "shot") of the spectral cube, a process suitable for fast changing objects. Known SSI devices exhibit large total track length (TTL), weight and production costs and relatively low optical throughput. We present a simple SSI camera based on a regular digital camera with (i) an added diffusing and dispersing "phase-only" static optical element at the entrance pupil ("diffuser") and (ii) tailored compressed sensing (CS) methods for digital processing of the diffused and dispersed (DD) image recorded on the image sensor. The diffuser is designed to mix the spectral cube data spectrally and spatially and thus to enable convergence in its reconstruction by CS-based algorithms. In addition to performing SSI, this SSI camera is capable to perform color imaging using a "monochromatic" or "gray-scale" image sensor without color filter arrays.

show abstract

“…Mosaic spectral filter arrays on an image sensor [2] lead to unacceptable light gathering losses and involve technological difficulties. The most straightforward way to perform SI is to use a removable set of narrow bandpass filters [3] or dynamic spectral filters [4]. High quality SI systems exploit "staring" or "pushbroom" imagers [5].…”

Section: Introductionmentioning

confidence: 99%

Spectral multiplexing method for digital snapshot spectral imaging

et al. 2009

View full text Add to dashboard Cite

We propose a spectral imaging method for piecewise "macropixel" objects, which allows a regular digital camera to be converted into a digital snapshot spectral imager by equipping the camera with only a disperser and a demultiplexing algorithm. The method exploits a "multiplexed spectrum" intensity pattern, i.e., the superposition of spectra from adjacent different image points, formed on the image sensor of the digital camera. The spatial image resolution is restricted to a macropixel level in order to acquire both spectral and spatial data (i.e., an entire spectral cube) in a single snapshot. Results of laboratory experiments with a special macropixel object image, composed of small, spatially uniform squares, provide to our knowledge a first verification of the proposed spectral imaging method.

show abstract

Sugar “Imaging” of Fruit Using a Low Cost Charge-Coupled Device Camera

Cited by 20 publications

References 9 publications

Near‐Infrared Hyperspectral Imaging in Food Research

Near‐Infrared Hyperspectral Imaging in Food Research

Snapshot Spectral and Color Imaging Using a Regular Digital Camera With a Monochromatic Image Sensor

Spectral multiplexing method for digital snapshot spectral imaging

Contact Info

Product

Resources

About