Background Segmentation and Dimensional Measurement of Corn Germplasm

Date
1995
Authors
Bern, Carl
Panigrahi, Suranjan
Misra, Manjit
Misra, Manjit
Bern, Carl
Marley, Stephen
Major Professor
Advisor
Committee Member
Journal Title
Journal ISSN
Volume Title
Publisher
Altmetrics
Authors
Research Projects
Organizational Units
Journal Issue
Series
Department
Agricultural and Biosystems Engineering
Abstract

An automatic thresholding technique was developed to segment the background from the images of corn germplasm (ears of corn). The technique was a modification of Otsu’s algorithm using probability theory. Three different measures were used to evaluate the performance of the modified Otsu’s algorithm for background segmentation and subsequent dimensional measurement of corn germplasm. Modified Otsu’s algorithm was found to perform better than Otsu’s algorithm and was successful in automatic background segmentation of all 80 images of corn germplasm included in the study. This modified algorithm also eliminated the misclassification of exposed cob in the image as background which occurred with Otsu’s algorithm. Subsequent dimensional measurements based on the segmentation by the modified algorithm were also highly accurate.

Comments

This article is from Transactions of the ASAE 38 (1995): 291–297, doi:10.13031/2013.27841. Posted with permission.

Description
Keywords
Citation
DOI
Collections