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Related Experiment Video

Updated: Jun 26, 2026

Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers

Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers

Published on: February 29, 2012

High-precision boundary length estimation by utilizing gray-level information.

Nataå A Sladoje¹, Joakim Lindblad

¹Faculty of Engineering, University of Novi Sad, Novi Sad, Serbia. sladoje@uns.ns.ac.yu

IEEE Transactions on Pattern Analysis and Machine Intelligence

|December 27, 2008

Summary

This study introduces a new method for accurately estimating object boundary length using pixel gray levels. The technique minimizes errors in digitized images, offering precise perimeter measurements for various shapes.

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Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

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Published on: January 5, 2024

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Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers

Enabling High Grayscale Resolution Displays and Accurate Response Time Measurements on Conventional Computers

Published on: February 29, 2012

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Area of Science:

Image processing and computer vision.
Computational geometry and measurement science.

Background:

Accurate object boundary length estimation is crucial in image analysis.
Traditional methods often struggle with digitization errors and pixel quantization.

Purpose of the Study:

To develop a novel, accurate, and precise method for estimating object boundary length.
To account for gray levels at object boundaries in digitized images.
To minimize estimation errors in quantized pixel value scenarios.

Main Methods:

A novel perimeter estimation method utilizing gray level information at object boundaries.
Mathematical derivation of optimal estimates minimizing maximal error for quantized pixel values.
Implementation via pseudocode, emphasizing ease of implementation and parallelization.

Main Results:

Error-free perimeter measurements for straight boundaries with non-quantized pixels.
Optimal estimates derived for quantized pixel values, converging to correct values with increasing gray levels.
Successful evaluation on concave and convex shapes at varying resolutions.

Conclusions:

The presented method offers an accurate and precise approach to perimeter estimation.
The technique is robust to pixel quantization and easy to implement and parallelize.
Demonstrated applicability on real images, outperforming other local approaches.