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Sensor for Distance Estimation Using FFT of Images.

José L Lázaro¹, Angel E Cano, Pedro R Fernández

¹Electronics Department, University of Alcalá, Superior Polytechnic School, University Campus, Alcalá de Henares (28871), Madrid, Spain; E-Mail: angel.cano@depeca.uah.es (A.E.C.)Telecommunication Department, University of Oriente, Av. de las Américas, SN, Santiago de Cuba (90900), Cuba; E-Mails: pedro.fernandez@depeca.uah.es (P.R.F.); caluna@depeca.uah.es (C.A.L.).

Sensors (Basel, Switzerland)

|February 4, 2012

Summary

This study presents a practical method for estimating distance to an infrared emitter diode (IRED) using camera pixel intensity. The developed model achieves over 3% accuracy for distances ranging from 420 to 800 cm.

Keywords:

Fast Fourier Transform artificial vision differential method distance estimation infrared zero-frequency component

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Area of Science:

Computer Vision
Optical Sensing
Metrology

Background:

Estimating distance from camera images is crucial for various applications.
Infrared emitter diodes (IREDs) are common light sources, but their distance estimation requires specific methods.
Pixel grey-level intensities are influenced by multiple factors that need to be accounted for.

Purpose of the Study:

To develop and validate a practical method for estimating the distance between an infrared emitter diode (IRED) and a camera.
To identify and model factors affecting pixel grey-level intensity for accurate distance calculation.
To assess the accuracy of the proposed distance estimation method.

Main Methods:

Defined key factors influencing grey-level intensity.
Related these factors to the zero-frequency component of the Fast Fourier Transform (FFT) image.
Developed and tested a general model using a differential methodology for distance estimation.
Validated the model over a range of 420 to 800 cm.

Main Results:

A methodology was established to estimate IRED-camera distance based on pixel intensity.
The relationship between image features and distance was modeled.
The differential methodology demonstrated accuracy exceeding 3% within the tested range.

Conclusions:

The proposed method provides a practical and accurate approach for non-contact distance estimation using IREDs and cameras.
The model effectively utilizes image intensity and FFT components for distance calculation.
The findings are applicable to systems requiring precise spatial measurement with infrared sources.