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United States Department of Agriculture

Agricultural Research Service

Research Project: Quality Based Inspection and Sorting of Specialty Crops Using Imaging and Physical Methods

Location: Healthy Processed Foods Research

Title: Methods for correcting morphological-based deficiencies in hyperspectral images of round objects

Authors
item Haff, Ronald
item Saranwong, Sirinnapa -
item Kawano, Sumio -

Submitted to: Near Infrared Reflectance International Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: June 7, 2011
Publication Date: N/A

Interpretive Summary: NIR images of curved surfaces contain undesirable effects due to the shape of the sample. A computer program was developed to remove the variation in pixel intensity based directly on well known physical effects involving light reflection and intensity. The ideal result would be a uniform image (as is appropriate for a uniform sample). The three predominant principles investigated are the behavior of light reflected from Lambertian surfaces, the 1/R2 relationship between light intensity and distance from the source, and the variation in arc length along a circle as seen from the detectors. Neglecting effects at the outer edge, pixel intensity variation was reduced from 110/255 to 18/255, or from 43 % to 7 %. The same principle can be applied to samples with circular cross sections along a particular axis, which includes many agricultural commodities. Contributing factors to the remaining pixel intensity variation error in the corrected images include specular reflection, unintended ambient light and reflections from surfaces, and line of sight issues that put portions of the sample out of view of the detectors.

Technical Abstract: NIR images of curved surfaces contain undesirable artifacts that are a consequence of the morphology, or shape of the sample. A software correction was developed to remove the variation in pixel intensity based directly on well known physical effects involving light reflection and intensity. The ideal result would be a uniform image (as is appropriate for a uniform sample). The three predominant principles investigated are the behavior of light reflected from Lambertian surfaces, the 1/R2 relationship between light intensity and distance from the source, and the variation in arc length along a circle as seen from the detectors. Neglecting effects at the outer edge, pixel intensity variation was reduced from 110/255 to 18/255, or from 43 % to 7 %. The same principle can be applied to samples with circular cross sections along a particular axis, which includes many agricultural commodities. Contributing factors to the remaining pixel intensity variation error in the corrected images include specular reflection, unintended ambient light and reflections from surfaces, and line of sight issues that put portions of the sample out of view of the detectors.

Last Modified: 7/24/2014