Enhanced Region-specific Algorithm: Image Quality Analysis for Digital Kirlian Effect

Lee, Razak Mohd Ali; Alipal, J.

doi:10.1109/cspa.2019.8696037

Cited by 1 publication

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, image processing has also been used by other previous researchers [13]- [15]. For example, Lee et al [16] employed gas discharge visualization (GDV) for imaging techniques that are captured by biophotons and then emitted by the human body; this method is quite good for the quality of the reconstructed image [17]. Another research conducted by Poojay and Srinivas [18] reviewed various researchers about image analysis based on aura images.…”

Section: Introductionmentioning

confidence: 99%

Aura detection using thermal camera with convolutional neural network method for mental health diagnosis

Ariswati

Soetjiatie

2023

IJEECS

View full text Add to dashboard Cite

Mental health is an important aspect in realizing overall health. For this reason, non-invasive medical equipment is needed for people with mental disorders. This study aimed to create a psychological health diagnostic tool by detecting auras using a thermal camera from facial objects. The contribution of this study is that the tool can detect the patient's aura without physical contact so that the patient is more comfortable and does not feel invaded. This research designed a system for detecting electromagnetic wave radiation energy emitted by the body using a thermal camera. Face detection in the input image was performed using a convolutional neural network (CNN) model single shot multibox detector (SSD), which is one of the CNN models that implements a bounding box to estimate the localization of detected objects. In this case, system testing was used to evaluate the performance of the CNN system algorithm for aura detection in terms of color (main color or average color). The results obtained were detectibility by 80%, selectivity by 88.88%, precision by 70%, sensitivity by 87.5%, and accuracy by 63.63%. The design of the aura detection system in this study will make it easier for psychiatrists and psychologists to help make a noninvasive diagnosis.

show abstract