Recent results in the grading of vegetative cuttings using computer vision

Author

Singh, Sanjiv ; Montemerio, M.

Author_Institution

Field Robotics Center, Carnegie Mellon Univ., Pittsburgh, PA, USA

Volume

3

fYear

1997

fDate

7-11 Sep 1997

Firstpage

1845

Abstract

This paper reports on recent progress in the development of system to group populations of vegetative cuttings. The system is required to assign a classification to cuttings such that they appear uniform after a growing period using single two-dimensional monochrome images. We have developed a fast segmentation technique that is able to measure plant features and a supervised learning scheme that learns a mapping from the features to a scalar classification. We report results based on segmentation of over 2000 geranium cuttings. The system is able to process images at 2 Hz and has an accuracy of over 90%. Both metrics exceed human performance

Keywords

agriculture; computer vision; image classification; image segmentation; learning (artificial intelligence); 2D monochrome images; computer vision; geranium; grading; pattern classification; scalar classification; segmentation; supervised learning; vegetative cuttings; Computer vision; Containers; Electrical equipment industry; Humans; Image segmentation; Optical propagation; Packaging; Reactive power; Robots; Supervised learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Robots and Systems, 1997. IROS '97., Proceedings of the 1997 IEEE/RSJ International Conference on

Conference_Location

Grenoble

Print_ISBN

0-7803-4119-8

Type

conf

DOI

10.1109/IROS.1997.656613

Filename

656613