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University of Illinois at Urbana-Champaign

Detection of stress cracks in corn kernels using machine vision

Abstract

dc:description

Maintaining high quality of corn is very important to both corn producers and buyers. The detection of stress cracks remains one of the most important tasks in corn quality inspection. Such an index of quality would be helpful in assessing not only the end-use values of the corn but also the drying method used and the appropriateness of subsequent handling procedures.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Agricultural Engineering
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kim, Chul-Soo
Contributors dc:contributor
  • Reid, John F.

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • Copyright 1991 Kim, Chulsoo
Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
AAI9124440
(UMI)AAI9124440
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/20995

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kim, Chul-Soo. Detection of stress cracks in corn kernels using machine vision. Dissertation thesis, University of Illinois at Urbana-Champaign, 2011. http://hdl.handle.net/2142/20995