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Related Experiment Video

Updated: May 29, 2026

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

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Published on: April 16, 2017

Scale preserving smoothing of polygons.

R L Kashyap¹, B J Oommen

¹School of Electrical Engineering, Purdue University, West Lafayette, IN 47907.

IEEE Transactions on Pattern Analysis and Machine Intelligence

|August 27, 2011

Summary

This study introduces a scale-preserving smoothing algorithm for polygons. The algorithm generates a linear minimum perimeter polygon (LMPP) that approximates the original shape while preserving scale information.

Area of Science:

Computational Geometry
Computer Graphics
Image Processing

Background:

Polygon simplification is crucial for efficient data representation.
Existing methods may alter scale information or introduce artifacts.
Need for algorithms that preserve scale and translation invariance.

Purpose of the Study:

To present a novel scale-preserving polygon smoothing algorithm.
To introduce the concept of Linear Minimum Perimeter Polygon (LMPP).
To enable controlled approximation of polygons.

Main Methods:

Developed a smoothing algorithm taking a polygon as input.
Defined LMPP as a smoothed polygon approximating the original within a tolerance.
Utilized a control parameter for the degree of approximation.

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Last Updated: May 29, 2026

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

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Main Results:

The algorithm outputs a smoothed polygon (LMPP) preserving scale information.
The resulting LMPP representation is invariant to scale and translation.
Demonstrated smoothing maps and character examples.

Conclusions:

The proposed algorithm effectively smooths polygons while preserving essential scale information.
LMPP offers a robust representation for approximated polygons.
The method provides controllable approximation and invariance properties.