Dense segmentation of textured fruits in video sequences

Waqar S. Qureshi, Shin'ichi Satoh, Matthew N. Dailey, Mongkol Ekpanyapong

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

9 Citations (Scopus)

Abstract

Autonomous monitoring of fruit crops based on mobile camera sensors requires methods to segment fruit regions from the background in images. Previous methods based on color and shape cues have been successful in some cases, but the detection of textured green fruits among green plant material remains a challenging problem. A recently proposed method uses sparse keypoint detection, keypoint descriptor computation, and keypoint descriptor classification followed by morphological techniques to fill the gaps between positively classified keypoints. We propose a textured fruit segmentation method based on super-pixel oversegmentation, dense SIFT descriptors, and and bag-of-visual-word histogram classification within each super-pixel. An empirical evaluation of the proposed technique for textured fruit segmentation yields a 96:67% detection rate, a per-pixel accuracy of 97:657%, and a per frame false alarm rate of 0:645%, compared to a detection rate of 90:0%, accuracy of 84:94%, and false alarm rate of 0:887% for the baseline sparse keypoint-based method. We conclude that super-pixel oversegmentation, dense SIFT descriptors, and bag-of-visual-word histogram classification are effective for in-field segmentation of textured green fruits from the background.

Original languageEnglish
Title of host publicationVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
PublisherSciTePress
Pages441-447
Number of pages7
ISBN (Print)9789897580048
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event9th International Conference on Computer Vision Theory and Applications, VISAPP 2014 - Lisbon, Portugal
Duration: 5 Jan 20148 Jan 2014

Publication series

NameVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
Volume2

Conference

Conference9th International Conference on Computer Vision Theory and Applications, VISAPP 2014
Country/TerritoryPortugal
CityLisbon
Period5/01/148/01/14

Keywords

  • Dense Classification
  • Super-pixels
  • Visual Word Histograms

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