LASER POINTER DETECTION BASED ON INTENSITY PROFILE ANALYSIS FOR APPLICATION IN TELECONSULTATION

Telemedicine is application of electronic communication to deliver medical care remotely. An important aspect of telemedicine is teleconsultation which involves obtaining the professional opinion of a healthcare provider. One of the ways to improve eleconsultation is to equip the remote specialist v...

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Bibliographic Details
Main Authors: NAIREEN IMTIAZ, MOHD MARZUKI MUSTAFA, AINI HUSSAIN, EDGAR SCAVINO
Format: Article
Language:English
Published: Taylor's University 2017-08-01
Series:Journal of Engineering Science and Technology
Subjects:
Online Access:http://jestec.taylors.edu.my/Vol%2012%20issue%208%20August%202017/12_8_17.pdf
Description
Summary:Telemedicine is application of electronic communication to deliver medical care remotely. An important aspect of telemedicine is teleconsultation which involves obtaining the professional opinion of a healthcare provider. One of the ways to improve eleconsultation is to equip the remote specialist via control of a laser pointer, located in the consultation area to provide a means of gesture. As such, accurate detection of laser spot is crucial in such systems as they rely on visual feedback, which enables the specialist in a remote site to control and point the laser in the active location using a standard mouse. The main issue in laser spot detection in a natural environment is the distinguishability of a laser point image from other bright regions and glare due to camera saturation. This problem remains unsolved without extensive computing and use of hardware filters. In this paper a hybrid algorithm is described which is aimed to work with natural indoor environment while limiting computation. This algorithm combines thresholding and blob evaluation methods with a novel image intensity profile comparison method based on linear regression. A comparison of the algorithm has been done with existing approaches. The developed algorithm shows a higher accuracy and faster execution time making it an ideal candidate for real time detection applications.
ISSN:1823-4690