Recognizing Plants Using Stochastic L-Systems

Authors

• Ashok K. Samal, University of Nebraska-LincolnFollow
• Brian Peterson, University of Nebraska-Lincoln
• David J. Holliday, University of Nebraska-Lincoln

Date of this Version

1994

Document Type

Article

Comments

Published in the Proceedings of the IEEE International Conference on Image Processing (ICIP-94), v. 1: 183-186. Copyright 1994, IEEE. Used by permission. DOI: 10.1109/ICIP.1994.413300

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.