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Spot Detection for Laser Sensors Based on Annular Convolution Filtering.

Lingjiang Li¹, Maolin Li^1,2, Weijun Sun^1,3

¹Guangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, Guangzhou 510006, China.

Sensors (Basel, Switzerland)

|April 28, 2023

Summary

This summary is machine-generated.

We developed annular convolution filtering (ACF) to accurately detect laser spots, even with background light interference. This method improves laser sensing for communication and measurement applications.

Keywords:

ACF image processing laser sensor spot detection

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Area of Science:

Optics and Photonics
Laser Technology
Image Processing

Background:

Laser spot detection is crucial for applications like communication and measurement.
Existing methods struggle with background light interference.
Robust spot detection requires improved signal processing techniques.

Purpose of the Study:

To propose a novel annular convolution filtering (ACF) method for accurate laser spot detection.
To overcome the limitations of existing methods in handling background light.
To enhance the reliability of laser sensing systems.

Main Methods:

Region of interest (ROI) identification using pixel statistical properties.
Annular convolution filtering based on laser energy attenuation.
Feature similarity index for laser spot parameter estimation.

Main Results:

ACF demonstrated superior performance in detecting laser spots across diverse background light conditions.
The method effectively mitigates interference from background light.
Experimental results validated ACF against standard, market, and benchmark methods (AAMED, ALS).

Conclusions:

Annular convolution filtering (ACF) offers a robust solution for laser spot detection.
The proposed method significantly improves accuracy and reduces background light interference.
ACF provides a valuable advancement for laser sensing technologies.