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Computing perimeters of regions in images represented by quadtrees
1Department of Computer Science, University of Maryland, College Park, MD 20742.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
Summary
This study introduces an efficient algorithm for calculating the perimeter of binary image regions using quadtrees. The method ensures each boundary segment is processed once, offering a time complexity linked to the quadtree
Area of Science:
- Computer Vision
- Image Processing
- Computational Geometry
Background:
- Calculating the perimeter of image regions is crucial for image analysis.
- Quadtrees offer an efficient hierarchical data structure for representing images.
Purpose of the Study:
- To develop and analyze an algorithm for computing the total perimeter of a region in a binary image represented by a quadtree.
- To ensure efficient boundary traversal and determine the algorithm's computational complexity.
Main Methods:
- An algorithm is presented that traverses the boundary segments of a region represented by a quadtree.
- The algorithm is designed to visit each boundary segment exactly once.
Main Results:
- The developed algorithm successfully computes the total perimeter of a quadtree-represented binary image region.
- Average execution time of the algorithm is shown to be proportional to the number of leaf nodes in the quadtree.
Conclusions:
- The proposed algorithm provides an efficient method for perimeter computation in quadtree-based image representations.
- The linear relationship between execution time and leaf nodes suggests scalability for image processing tasks.
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