Prof. Renfu Lu Profile

Prof. Renfu Lu

Research Leader at Agriculture Research Service

SPIE Involvement:

Conference Program Committee | Author

Publications (22)

Proceedings Article | 1 May 2017 Presentation + Paper

Presentation + Paper

Finite element simulation of light transfer in turbid media under structured illumination

Dong Hu, Renfu Lu, Yibin Ying

Proceedings Volume 10217, 102170B (2017) https://doi.org/10.1117/12.2263121

KEYWORDS: Diffuse reflectance spectroscopy, Reflectivity, Testing and analysis, Spatial frequencies, Optical properties, Light scattering, Monte Carlo methods, Scattering, Finite element methods, Geometrical optics, Chemical elements, Diffusion, Absorption, Tissues, Biological research

Read Abstract +

Proceedings Article | 1 May 2017 Presentation + Paper

Presentation + Paper

Development of a multichannel hyperspectral imaging probe for food property and quality assessment

Yuping Huang, Renfu Lu, Kunjie Chen

Proceedings Volume 10217, 102170L (2017) https://doi.org/10.1117/12.2262622

KEYWORDS: Absorption, Reflectivity, Transmittance, Optical testing, Imaging systems, Liquids, Hyperspectral imaging, Calibration, Optical properties, Spectral calibration, Light sources, Light, Scattering, Signal detection, Light scattering

Read Abstract +

Proceedings Article | 1 May 2017 Presentation + Paper

Presentation + Paper

Phase analysis for three-dimensional surface reconstruction of apples using structured-illumination reflectance imaging

Yuzhen Lu, Renfu Lu

Proceedings Volume 10217, 102170G (2017) https://doi.org/10.1117/12.2262339

KEYWORDS: 3D profiling, Phase shifting, Calibration, Imaging systems, Cameras, Projection systems, Analytical research, Defect detection, Digital Light Processing, Demodulation

Read Abstract +

Proceedings Article | 17 May 2016 Paper

Paper

Detection of fresh bruises in apples by structured-illumination reflectance imaging

Yuzhen Lu, Richard Li, Renfu Lu

Proceedings Volume 9864, 986406 (2016) https://doi.org/10.1117/12.2225148

KEYWORDS: Reflectivity, Demodulation, Tissues, Visualization, Projection systems, Spatial frequencies, Hyperspectral imaging, Telescopic pixel displays, Cameras, Agriculture

Read Abstract +

Proceedings Article | 17 May 2016 Paper

Paper

A sequential method for measuring the optical properties of two-layer media with spatially-resolved diffuse reflectance: simulation study

Aichen Wang, Renfu Lu, Lijuan Xie

Proceedings Volume 9864, 98640Q (2016) https://doi.org/10.1117/12.2225104

KEYWORDS: Scattering, Optical properties, Diffuse reflectance spectroscopy, Reflectivity, Diffusion, Tissues, Statistical analysis, Error analysis, Photons, Monte Carlo methods

Read Abstract +

Proceedings Article | 3 June 2011 Paper

Paper

Peach maturity/quality assessment using hyperspectral imaging-based spatially resolved technique

Haiyan Cen, Renfu Lu, Fernando Mendoza, Diwan Ariana

Proceedings Volume 8027, 80270L (2011) https://doi.org/10.1117/12.883573

KEYWORDS: Optical properties, Absorption, Skin, Scattering, Reflectivity, Hyperspectral imaging, Light scattering, Fermium, Frequency modulation, Optical testing

Read Abstract +

Proceedings Article | 3 June 2011 Paper

Paper

Multi-sensor data fusion for improved prediction of apple fruit firmness and soluble solids content

Fernando Mendoza, Renfu Lu, Haiyan Cen

Proceedings Volume 8027, 80270M (2011) https://doi.org/10.1117/12.883649

KEYWORDS: Scattering, Near infrared, Sensors, Atrial fibrillation, Acoustics, Calibration, Solids, Data fusion, Data modeling, Near infrared spectroscopy

Read Abstract +

Several nondestructive technologies have been developed for assessing the firmness and soluble solids content (SSC) of apples. Each of these technologies has its merits and limitations in predicting the two quality parameters. With the concept of multi-sensor data fusion, different sensors would work synergistically and complementarily to improve the quality prediction of apples. In this research, four sensing systems (i.e., an acoustic sensor, a bioyield firmness tester, a miniature near-infrared (NIR) spectrometer, and an online hyperspectral scattering system) were evaluated and combined for nondestructive prediction of firmness and SSC of 'Jonagold' (JG), 'Golden Delicious' (GD), and 'Delicious' (RD) apples. A total of 6,535 apples harvested in 2009 and 2010 were used for analysis. Each of the four sensors showed various degrees of ability to predict apple quality. Better predictions of the firmness and, in most cases, of the SSC were obtained using sensors fusion than using individual sensors, as measured by number of latent variables, correlation coefficient, and standard error of prediction (SEP). Results obtained from the two harvest seasons with the multi-sensor fusion approach were quite consistent, confirming the validity and robustness of the proposed approach. The SEPs for firmness measurement of JG, GD and RD using the best combination of two-sensor data were reduced by 13.3, 19.7 and 7.9% for the 2009 data and 16.0, 12.6 and 4.7% for the 2010 data; and using all four-sensor data by 21.8, 25.6 and 13.6% in 2009, and 14.9, 21.9, and 7.9% in 2010, respectively. For SSC prediction, using the two-sensor data (i.e., NIR and scattering) improved predictions for JG, GD and RD apples harvested in 2009, with their SEP values being reduced by 10.4, 6.6 and 6.8%, respectively. This research demonstrated that the fused systems provided more complete complementary information and, thus, were more powerful than individual sensors in prediction of apple quality.

Proceedings Article | 3 June 2011 Paper

Paper

Detection of fruit fly infestation in pickling cucumbers using hyperspectral imaging

Renfu Lu, Diwan Ariana

Proceedings Volume 8027, 80270K (2011) https://doi.org/10.1117/12.887524

KEYWORDS: Transmittance, Reflectivity, Hyperspectral imaging, Inspection, Imaging systems, Tissues, Image processing, Image classification, Visualization, Glasses

Read Abstract +

Proceedings Article | 24 April 2010 Paper

Paper

Characterization of the optical properties of normal and defective pickling cucumbers and whole pickles

Renfu Lu, Diwan Ariana, Haiyan Cen

Proceedings Volume 7676, 76760G (2010) https://doi.org/10.1117/12.852636

KEYWORDS: Scattering, Absorption, Hyperspectral imaging, Optical properties, Tissues, Diffusion, Light scattering, Imaging systems, Agriculture, Translucency

Read Abstract +

Internal defect in pickling cucumbers can cause bloater damage during brining, which lowers the quality of final pickled products and results in economic loss for the pickle industry. Hence it is important to have an effective optical inspection system for detection and segregation of defective pickling cucumbers. This research was intended to measure the spectral absorption and scattering properties of normal and internally defective pickling cucumbers and whole pickles, using hyperspectral imaging-based spatially-resolved technique. Spatially-resolved hyperspectral scattering images were acquired from 50 freshly harvested 'Journey' pickling cucumbers in the summer of 2008. The cucumbers were then subjected to rolling under mechanical load to induce internal damage. The damaged cucumbers were imaged again one hour and one day after the mechanical stress treatment. In addition, 20 whole pickles each of normal and defective (bloated) class were also measured by following the same procedure as that for pickling cucumbers. Spectra of the absorption and reduced scattering coefficients for pickling cucumbers and whole pickles were extracted from the spatially-resolved scattering profiles, using an inverse algorithm for a diffusion theory model, for the spectral range of 700-1,000 nm. It was found that within one hour after mechanical damage, changes in the absorption and reduced scattering coefficients for the cucumbers were minimal. One day after mechanical damage, the absorption coefficient for the cucumbers increased noticeably for the wavelengths of 700-920 nm, whereas the reduced scattering coefficient decreased more significantly for the wavelengths of 700-1,000 nm. Overall mechanical damage had greater impact on the scattering properties than on the absorption properties. After brining, pickles became translucent and scattering was greatly diminished. Thus the diffusion theory model was no longer valid for determining the optical properties of whole pickles. This research suggests that effective defect detection may be achieved by enhancing scattering features in the optical evaluation of cucumbers.

Proceedings Article | 28 April 2009 Paper

Paper

Analysis of hyperspectral scattering characteristics for predicting apple fruit firmness and soluble solids content

Renfu Lu, Min Huang, Jianwei Qin

Proceedings Volume 7315, 73150I (2009) https://doi.org/10.1117/12.819287

KEYWORDS: Scattering, Calibration, Light scattering, Diffusion, Reflectivity, Absorption, Hyperspectral imaging, Solids, Solid modeling, Statistical modeling

Read Abstract +

SPIE Journal Paper | 1 December 2007

Development of a multispectral imaging prototype for real-time detection of apple fruit firmness

Renfu Lu, Yankun Peng

OE, Vol. 46, Issue 12, 123201, (December 2007) https://doi.org/10.1117/12.10.1117/1.2818812

KEYWORDS: Scattering, Laser scattering, Light scattering, Multispectral imaging, Prototyping, Imaging systems, Calibration, Near infrared, Reflectivity, Image processing

Read Abstract +

Proceedings Article | 12 October 2007 Paper

Paper

A recursive method for updating apple firmness prediction models based on spectral scattering images

Yankun Peng, Renfu Lu

Proceedings Volume 6761, 67610U (2007) https://doi.org/10.1117/12.731351

KEYWORDS: Scattering, Statistical modeling, Calibration, Light scattering, Multispectral imaging, Lutetium, Performance modeling, Spectral models, Imaging systems, Error analysis

Read Abstract +

Proceedings Article | 12 October 2007 Paper

Paper

Internal quality evaluation of apples using spectral absorption and scattering properties

Jianwei Qin, Renfu Lu, Yankun Peng

Proceedings Volume 6761, 67610M (2007) https://doi.org/10.1117/12.751937

KEYWORDS: Scattering, Absorption, Hyperspectral imaging, Calibration, Imaging systems, Light scattering, Optical properties, Agriculture, Solids, Data modeling

Read Abstract +

Proceedings Article | 23 October 2006 Paper

Paper

Integrating fluorescence and interactance measurements to improve apple maturity assessment

Hyun Kwon Noh, Renfu Lu

Proceedings Volume 6381, 63810M (2006) https://doi.org/10.1117/12.685973

KEYWORDS: Luminescence, Skin, Spectroscopy, Integrated modeling, Statistical modeling, Solids, Data modeling, Solid modeling, Reflectivity, Ultraviolet radiation

Read Abstract +

Proceedings Article | 9 November 2005 Paper

Paper

A laser-based multispectral imaging system for real-time detection of apple fruit firmness

Renfu Lu, Yankun Peng

Proceedings Volume 5996, 59960F (2005) https://doi.org/10.1117/12.630814

KEYWORDS: Scattering, Laser scattering, Multispectral imaging, Light scattering, Imaging systems, Prototyping, Image processing, Charge-coupled devices, Calibration, Reflectivity

Read Abstract +

Proceedings Article | 9 November 2005 Paper

Paper

Hyperspectral diffuse reflectance for determination of the optical properties of milk and fruit and vegetable juices

Jianwei Qin, Renfu Lu

Proceedings Volume 5996, 59960Q (2005) https://doi.org/10.1117/12.630691

KEYWORDS: Scattering, Hyperspectral imaging, Absorption, Optical properties, Imaging systems, Reflectivity, Calibration, Data modeling, Light scattering, Diffuse reflectance spectroscopy

Read Abstract +

Proceedings Article | 9 November 2005 Paper

Paper

Detection of mechanical injury on pickling cucumbers using near-infrared hyperspectral imaging

D. Ariana, R. Lu, D. Guyer

Proceedings Volume 5996, 59960P (2005) https://doi.org/10.1117/12.629594

KEYWORDS: Hyperspectral imaging, Tissues, Imaging systems, Reflectivity, Image segmentation, Injuries, Cameras, Data modeling, Statistical modeling, Instrument modeling

Read Abstract +

Proceedings Article | 9 November 2005 Paper

Paper

UV/blue light-induced fluorescence for assessing apple maturity

Hyun Kwon Noh, Renfu Lu

Proceedings Volume 5996, 59960I (2005) https://doi.org/10.1117/12.629901

KEYWORDS: Luminescence, Calibration, Skin, Data modeling, Fluorescence spectroscopy, Spectroscopy, Ultraviolet radiation, Solids, Quality measurement, Near infrared spectroscopy

Read Abstract +

Proceedings Article | 19 November 2004 Paper

Paper

A liquid-crystal-tunable-filter-based multispectral imaging system for prediction of apple fruit firmness

Yankun Peng, Renfu Lu

Proceedings Volume 5587, (2004) https://doi.org/10.1117/12.571382

KEYWORDS: Scattering, Light scattering, Calibration, Multispectral imaging, Imaging systems, Near infrared spectroscopy, Spectroscopy, Light sources, Tunable filters, Liquid crystals

Read Abstract +

Proceedings Article | 19 November 2004 Paper

Paper

Detecting pits in tart cherries by hyperspectral transmission imaging

Jianwei Qin, Renfu Lu

Proceedings Volume 5587, (2004) https://doi.org/10.1117/12.571359

KEYWORDS: Hyperspectral imaging, Neural networks, Defect detection, Principal component analysis, Imaging systems, Lutetium, Algorithm development, Inspection, Imaging spectroscopy, Agriculture

Read Abstract +

Proceedings Article | 30 March 2004 Paper

Paper

Near-infrared multispectral scattering for assessing internal quality of apple fruit

Renfu Lu

Proceedings Volume 5271, (2004) https://doi.org/10.1117/12.516008

KEYWORDS: Scattering, Light scattering, Multispectral imaging, Imaging systems, Laser scattering, Neural networks, Neurons, Calibration, Solids, Near infrared spectroscopy

Read Abstract +

Proceedings Article | 12 January 1999 Paper

Paper

Hyperspectral imaging for safety inspection of food and agricultural products

Renfu Lu, Yud-Ren Chen

Proceedings Volume 3544, (1999) https://doi.org/10.1117/12.335771

KEYWORDS: Hyperspectral imaging, Imaging spectroscopy, Safety, Inspection, Imaging systems, Reflectivity, Spectroscopy, Food inspection, Agriculture, Sensors

Read Abstract +

Showing 5 of 22 publications

Conference Committee Involvement (22)

Sensing for Agriculture and Food Quality and Safety XVI

22 April 2024 | National Harbor, Maryland, United States

Sensing for Agriculture and Food Quality and Safety XV

2 May 2023 | Orlando, Florida, United States

Sensing for Agriculture and Food Quality and Safety XIV

5 April 2022 | Orlando, Florida, United States

Sensing for Agriculture and Food Quality and Safety XIII

12 April 2021 | Online Only, Florida, United States

Sensing for Agriculture and Food Quality and Safety XII

27 April 2020 | Online Only, California, United States

Sensing for Agriculture and Food Quality and Safety XI

16 April 2019 | Baltimore, MD, United States

Sensing for Agriculture and Food Quality and Safety X

17 April 2018 | Orlando, FL, United States

Sensing for Agriculture and Food Quality and Safety IX

13 April 2017 | Anaheim, CA, United States

Sensing for Agriculture and Food Quality and Safety VIII

20 April 2016 | Baltimore, MD, United States

Sensing for Agriculture and Food Quality and Safety VII

21 April 2015 | Baltimore, MD, United States

Sensing for Agriculture and Food Quality and Safety VI

6 May 2014 | Baltimore, MD, United States

Sensing for Agriculture and Food Quality and Safety V

30 April 2013 | Baltimore, Maryland, United States

Sensing Technologies for Biomaterial, Food, and Agriculture 2013

23 April 2013 | Yokohama, Japan

Sensing for Agriculture and Food Quality and Safety IV

24 April 2012 | Baltimore, Maryland, United States

Sensing for Agriculture and Food Quality and Safety III

26 April 2011 | Orlando, Florida, United States

Sensing for Agriculture and Food Quality and Safety II

6 April 2010 | Orlando, Florida, United States

Sensing for Agriculture and Food Quality and Safety

14 April 2009 | Orlando, Florida, United States

Special Sessions on Food Safety, Visual Analytics, Resource Restricted Embedded and Sensor Networks, and 3D Imaging and Display

17 March 2008 | Orlando, Florida, United States

Optics for Natural Resources, Agriculture, and Foods II

10 September 2007 | Boston, MA, United States

Optics for Natural Resources, Agriculture, and Foods

3 October 2006 | Boston, Massachusetts, United States

Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality

23 October 2005 | Boston, MA, United States

Nondestructive Sensing for Food Safety, Quality, and Natural Resources

26 October 2004 | Philadelphia, Pennsylvania, United States

Showing 5 of 22 Conference Committees

SIGN IN TO:

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Advertisement

Advertisement