Abstract
In this paper, we have presented a new method for computing the best-fitted rectangle for closed regions using their boundary points. The vertices of the best-fitted rectangle are computed using a bisection method starting with the upper-estimated rectangle and the under-estimated rectangle. The vertices of the upper- and under-estimated rectangles are directly computed using closed-form solutions by solving for pairs of straight lines. Starting with these two rectangles, we solve for the best-fitted rectangle iteratively using a bisection method. The algorithm stops when the areas of the fitted rectangles remain unchanged during consecutive iterations. Extensive evaluation of our algorithm demonstrates its effectiveness.
Original language | English (US) |
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Pages (from-to) | 1263-1271 |
Number of pages | 9 |
Journal | Machine Vision and Applications |
Volume | 23 |
Issue number | 6 |
DOIs | |
State | Published - Nov 2012 |
Keywords
- Centroid
- Least square method
- Major axis
- Minimum bounding box
- Minor axis
- Orientation
- Rectangular fit
- Segmentation
- Shape features
ASJC Scopus subject areas
- Software
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Computer Science Applications