Vegetation segmentation in cornfield images using bag of words

Yerania Campos, Erik Rodner, Joachim Denzler, Humberto Sossa, Gonzalo Pajares

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

We provide an alternative methodology for vegetation segmentation in cornfield images. The process includes two main steps, which makes the main contribution of this approach: (a) a low-level segmentation and (b) a class label assignment using Bag of Words (BoW) representation in conjunction with a supervised learning framework. The experimental results show our proposal is adequate to extract green plants in images of maize fields. The accuracy for classification is 95.3% which is comparable to values in current literature.

Original languageEnglish
Title of host publicationAdvanced Concepts for Intelligent Vision Systems - 17th International Conference, ACIVS 2016, Proceedings
EditorsCosimo Distante, Dan Popescu, Paul Scheunders, Wilfried Philips, Jacques Blanc-Talon
PublisherSpringer Verlag
Pages193-204
Number of pages12
ISBN (Print)9783319486796
DOIs
StatePublished - 2016
Event17th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2016 - Lecce, Italy
Duration: 24 Oct 201627 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10016 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2016
Country/TerritoryItaly
CityLecce
Period24/10/1627/10/16

Keywords

  • Bag-of-Words
  • Colour Vegetation Indices
  • Green detection
  • Machine learning

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