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A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
Binary partition tree analysis based on region evolution and its application to tree simplification
Huihai Lu1, John C Woods, Mohammed Ghanbari
1Department of Electronics Systems Engineering, University of Essex, CO4 3SQ, Colchester, Essex, UK. hlu@essex.ac.uk
Summary
This study introduces a novel framework for analyzing binary partition trees using evolvement functions and a knee function to model image property changes. The method simplifies trees by pruning reluctant merges, preserving image details while significantly reducing nodes for image analysis and segmentation.
Area of Science:
- Computer Vision
- Image Analysis
- Data Structures
Background:
- Pyramid image representations utilize tree structures for region-based analysis.
- Binary partition trees document merging processes, storing image property change histories from leaf to root nodes.
Purpose of the Study:
- To develop a novel framework for binary partition tree analysis.
- To model image property change histories using evolvement functions and analyze their statistics with a knee function.
- To demonstrate tree simplification while preserving image details.
Main Methods:
- Modeling change histories with evolvement functions.
- Analyzing second-order statistics using a knee function to identify reluctant merges.
- Implementing a tree simplification method by pruning nodes associated with the first reluctant merge.
Main Results:
- A novel framework for binary partition tree analysis was formulated.
- Tree simplification significantly reduced the number of nodes while preserving image details.
- An image filtering tool preserving object boundaries was developed, applicable to segmentation tasks.
Conclusions:
- The proposed framework offers an effective method for binary partition tree simplification.
- The approach reduces solution space and computational complexity.
- The resulting image filtering tool demonstrates practical applications in image segmentation.
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