Prediction Model of Alcohol Intoxication from Facial Temperature Dynamics Based on K-Means Clustering Driven by Evolutionary Computing

Kubíček, Jan; Vilímek, Dominik; Krestanova, Alice; Penhaker, Marek; Kotalova, Eva; Faure-Brac, Bastien; Noel, Clément; Ščurek, Radomír; Augustýnek, Martin; Cerny, Martin; Kantor, Tomas

doi:10.3390/sym11080995

Cited by 10 publications

(3 citation statements)

References 49 publications

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“…The proposed method's e cacy was exhibited by the experiential outcomes. Jan Kubicek et al [21] utilized the segmentation model for facial temperature feature extraction as of the IR (infrared radiation) images centered on the clustering algorithm. The algorithm utilizes the modi ed Arti cial Bee Colony (ABC) optimization.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Iris Segmentation and Classification of Drunk Person Using Modified Circle Hough Transform

Jayadev¹,

Bellary²

2022

Preprint

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With various publications for Iris Recognition (IR) in the past few years, a more attractive research topic is Biometrics. Deformation in the iris pattern is created when the pupil dilates/constricts owing to alcohol consumption probably affecting IR performance. The eye's pupil region was not segmented by the prevailing segmentation schemes along with having low accuracy. An efficient iris segmentation model along with clustering the drunk person utilizing a Modified Circle Hough Transform (MCHT) was proposed in this scheme to tackle those issues. Noise reduction, iris segmentation, pupil segmentation and drink and no-drink person’s clustering are the steps comprised in the proposed model. The input images are gathered from the database initially. The noise is abated from the image by utilizing Median Filtering (MF). The Canny Mathematical Morphology (CMM) was employed to segment the iris part from the noise-free image. Subsequently, the MCHT executed the pupil segmentation as of the segmented iris image. The system’s accuracy along with robustness is elevated by performing this alteration. Consequently, the Matrix Based Clustering (MBC) clustered the drinker and the non-drinker person. The experiential outcomes exhibit that better performance was proved by the proposed method than the top-notch models.

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Section: Related Workmentioning

confidence: 99%

An Efficient Iris Segmentation and Classification of Drunk Person Using Modified Circle Hough Transform

Jayadev¹,

Bellary²

2022

Preprint

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“…The random solutions of ABC algorithm are created. The corresponding computation method [47] can be written by (23). The maximum iteration is also set, and the initial iteration number is 0.…”

Section: (A)mentioning

confidence: 99%

“…The random solutions of ABC algorithm are created. The corresponding computation method [47] can be written by (23).…”

Section: (A)mentioning

confidence: 99%

Multi-UAV Optimal Mission Assignment and Path Planning for Disaster Rescue Using Adaptive Genetic Algorithm and Improved Artificial Bee Colony Method

Liu

Wang

et al. 2021

Actuators

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An optimal mission assignment and path planning method of multiple unmanned aerial vehicles (UAVs) for disaster rescue is proposed. In this application, the UAVs include the drug delivery UAV, image collection UAV, and communication relay UAV. When implementing the modeling and simulation, first, three threat sources are built: the weather threat source, transmission tower threat source, and upland threat source. Second, a cost-revenue function is constructed. The flight distance, oil consumption, function descriptions of UAV, and threat source factors above are considered. The analytic hierarchy process (AHP) method is utilized to estimate the weights of cost-revenue function. Third, an adaptive genetic algorithm (AGA) is designed to solve the mission allocation task. A fitness function which considers the current and maximum iteration numbers is proposed to improve the AGA convergence performance. Finally, an optimal path plan between the neighboring mission points is computed by an improved artificial bee colony (IABC) method. A balanced searching strategy is developed to modify the IABC computational effect. Extensive simulation experiments have shown the effectiveness of our method.

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A Quantitative and Comparative Analysis of Edge Detectors for Biomedical Image Identification Within Dynamical Noise Effect

Vilímek

Kubikova

Kubíček

et al. 2020

Intelligent Information and Database Systems

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Prediction Model of Alcohol Intoxication from Facial Temperature Dynamics Based on K-Means Clustering Driven by Evolutionary Computing

Cited by 10 publications

References 49 publications

An Efficient Iris Segmentation and Classification of Drunk Person Using Modified Circle Hough Transform

An Efficient Iris Segmentation and Classification of Drunk Person Using Modified Circle Hough Transform

Multi-UAV Optimal Mission Assignment and Path Planning for Disaster Rescue Using Adaptive Genetic Algorithm and Improved Artificial Bee Colony Method

A Quantitative and Comparative Analysis of Edge Detectors for Biomedical Image Identification Within Dynamical Noise Effect

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