Early Results in the Grading of Vegetative Cuttings Using Computer Vision

Qiang Ji and Sanjiv Singh
Tech. Report, CMU-RI-TR-96-22, Robotics Institute, Carnegie Mellon University, May, 1996

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Commercial vegetative propagation of floricultural crops requires the segregation of plant cuttings into categories based on size. The cuttings however must be graded when they are planted (“stuck”), at which time the grade of a cutting is not easy to determine. This report describes a system that learns to classify cuttings from being shown examples of images of cuttings that have been graded by a human expert. Based on the example set, the system learns to grade cuttings into categories. We report the results based on a set of 150 geranium plants that were graded by our system and compare the results to the performance of an expert grader.

author = {Qiang Ji and Sanjiv Singh},
title = {Early Results in the Grading of Vegetative Cuttings Using Computer Vision},
year = {1996},
month = {May},
institution = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-96-22},
} 2017-09-13T10:50:32-04:00