3D surface scan of biological samples with a Push-broom Imaging Spectrometer

The food industry is always on the lookout for sensing technologies for rapid and nondestructive inspection of food products. Hyperspectral imaging technology integrates both imaging and spectroscopy into unique imaging sensors. Its application for food safety and quality inspection has made significant progress in recent years. Specifically, hyperspectral imaging has shown its potential for surface contamination detection in many food related applications. Most existing hyperspectral imaging systems use pushbroom scanning which is generally used for flat surface inspection. In some applications it is desirable to be able to acquire hyperspectral images on circular objects such as corn ears, apples, and cucumbers. Past research describes inspection systems that examine all surfaces of individual objects. Most of these systems did not employ hyperspectral imaging. These systems typically utilized a roller to rotate an object, such as an apple. During apple rotation, the camera took multiple images in order to cover the complete surface of the apple. The acquired image data lacked the spectral component present in a hyperspectral image. This paper discusses the development of a hyperspectral imaging system for a 3-D surface scan of biological samples. The new instrument is based on a pushbroom hyperspectral line scanner using a rotational stage to turn the sample. The system is suitable for whole surface hyperspectral imaging of circular objects. In addition to its value to the food industry, the system could be useful for other applications involving 3-D surface inspection.

[1]  F. Dowell,et al.  DETECTING AFLATOXIN IN SINGLE CORN KERNELS BY TRANSMITTANCE AND REFLECTANCE SPECTROSCOPY , 2001 .

[2]  Kurt C. Lawrence,et al.  Line-scan hyperspectral imaging system for real-time inspection of poultry carcasses with fecal material and ingesta , 2011 .

[3]  Y. R. Chen,et al.  HYPERSPECTRAL REFLECTANCE AND FLUORESCENCE IMAGING SYSTEM FOR FOOD QUALITY AND SAFETY , 2001 .

[4]  T. Cleveland,et al.  Resistance to aflatoxin accumulation in kernels of maize inbreds selected for ear rot resistance in West and Central Africa. , 2001, Journal of food protection.

[5]  Renfu Lu,et al.  Detection of bruises on apples using near-infrared hyperspectral imaging , 2003 .

[6]  Moon S Kim,et al.  Using parabolic mirrors for complete imaging of apple surfaces. , 2009, Bioresource technology.

[7]  Y. R. Chen,et al.  Hyperspectral-multispectral line-scan imaging system for automated poultry carcass inspection applications for food safety. , 2007, Poultry science.

[8]  G. Zavattini,et al.  A hyperspectral fluorescence imaging system for biological applications , 2003, 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515).

[9]  Colm P. O'Donnell,et al.  Hyperspectral imaging – an emerging process analytical tool for food quality and safety control , 2007 .

[10]  Zou Xiaobo,et al.  In-line detection of apple defects using three color cameras system , 2010 .

[11]  Vincent Leemans,et al.  A real-time grading method of apples based on features extracted from defects , 2004 .

[12]  W. R. Windham,et al.  Hyperspectral Imaging for Detecting Fecal and Ingesta Contaminants on Poultry Carcasses , 2002 .

[13]  Kurt C. Lawrence,et al.  Hyperspectral Imaging System for Identification of Fecal and Ingesta Contamination on Poultry Carcasses , 2001 .

[14]  D. L. Peterson,et al.  Identifying defects in images of rotating apples , 2005 .

[15]  D. Bhatnagar,et al.  Correlation and classification of single kernel fluorescence hyperspectral data with aflatoxin concentration in corn kernels inoculated with Aspergillus flavus spores , 2010, Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment.