Recognizing plants using stochastic L-systems

A. Samal, B. Peterson, D. J. Holliday

Research output: Contribution to journalConference article

7 Scopus citations

Abstract

Recognizing naturally occurring objects has been a difficult task in computer vision. One of the keys to recognizing objects is the development of a suitable model. One type of model, the fractal, has been used successfully to model complex natural objects. A class of fractals, the L-system, has not only been used to model natural plants, but has also aided in their recognition. This research extends the work in plant recognition using L-systems in two ways. Stochastic L-systems are used to model and generate more realistic plants. Furthermore, to handle the complexity of recognition, a learning system is used that automatically generates a decision tree for classification. Results indicate that the approach used here has great potential as a method for recognition of natural objects.

Original languageEnglish (US)
Article number413300
Pages (from-to)183-187
Number of pages5
JournalProceedings - International Conference on Image Processing, ICIP
Volume1
DOIs
StatePublished - 1994
EventProceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA
Duration: Nov 13 1994Nov 16 1994

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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