Kanika Bhalla¹, Deepika Koundal^2,*, Surbhi Bhatia³, Mohammad Khalid Imam Rahmani⁴, Muhammad Tahir⁴

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5503-5518, 2022, DOI:10.32604/cmc.2022.021125

Abstract Traditional techniques based on image fusion are arduous in integrating complementary or heterogeneous infrared (IR)/visible (VS) images. Dissimilarities in various kind of features in these images are vital to preserve in the single fused image. Hence, simultaneous preservation of both the aspects at the same time is a challenging task. However, most of the existing methods utilize the manual extraction of features; and manual complicated designing of fusion rules resulted in a blurry artifact in the fused image. Therefore, this study has proposed a hybrid algorithm for the integration of multi-features among two heterogeneous images. Firstly, fuzzification of two IR/VS… More >

K. M. Delphin Raj¹, Sun-Ho Yum¹, Jinyoung Lee², Eunbi Ko³, Soo-Yong Shin², Soo-Hyun Park^3,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5721-5743, 2022, DOI:10.32604/cmc.2022.020870

Abstract For the past few decades, the internet of underwater things (IoUT) obtained a lot of attention in mobile aquatic applications such as oceanography, diver network monitoring, unmanned underwater exploration, underwater surveillance, location tracking system, etc. Most of the IoUT applications rely on acoustic medium. The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate, attenuation, limited bandwidth, limited battery, limited memory, connectivity problem, etc. One of the significant applications of IoUT include monitoring underwater diver networks. In order to perform a reliable and energy-efficient… More >

Abderrezzaq Benalia^1,2, Kerroum Derbal^2,*, Amel Khalfaoui¹, Antonio Pizzi³, Ghouti Medjahdi⁴

Journal of Renewable Materials, Vol.10, No.3, pp. 625-637, 2022, DOI:10.32604/jrm.2022.017848

Abstract The purpose of this work is the study the ability of the plant material Aloe vera to act as natural coagulant using raw water obtained from a drinking water treatment plant (Mila, Algeria). Different solvents such as: NaCl; NaOH and HCl were used as chemical activators to extract the active components from the Aloe vera plant, and different coagulation-flocculation experiments were conducted in a jar test apparatus to evaluate the performance of the extracted coagulant. Also, the effect of coagulant dose on some water parameters such as turbidity, pH, total alkalinity and organic matter were investigated. The results showed that… More > Graphic Abstract

Simon Crase^1,2, Benjamin Hall², Suresh N. Thennadil^3,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1945-1965, 2021, DOI:10.32604/cmc.2021.018517

Abstract Supervised machine learning techniques have become well established in the study of spectroscopy data. However, the unsupervised learning technique of cluster analysis hasn’t reached the same level maturity in chemometric analysis. This paper surveys recent studies which apply cluster analysis to NIR and IR spectroscopy data. In addition, we summarize the current practices in cluster analysis of spectroscopy and contrast these with cluster analysis literature from the machine learning and pattern recognition domain. This includes practices in data pre-processing, feature extraction, clustering distance metrics, clustering algorithms and validation techniques. Special consideration is given to the specific characteristics of IR and… More >

Pingping Yu¹, Jiayu Wang¹, Ning Cao^2,*, Heiner Dintera³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3861-3876, 2021, DOI:10.32604/cmc.2021.017527

Abstract Along with the rapid development of biometric authentication technology, face recognition has been commercially used in many industries in recent years. However, it cannot be ignored that face recognition-based authentication techniques can be easily spoofed using various types of attacks such photographs, videos or forged 3D masks. In order to solve this problem, this work proposed a face anti-fraud algorithm based on the fusion of thermal infrared images and visible light images. The normal temperature distribution of the human face is stable and characteristic, and the important physiological information of the human body can be observed by the infrared thermal… More >

Peizhou Yan¹, Jiancheng Zou^2,*, Zhengzheng Li¹, Xin Yang³

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 213-225, 2021, DOI:10.32604/iasc.2021.016201

Abstract Within the application of driving assistance systems, the detection of driver’s facial features in the cab for a spectrum of luminosities is mission critical. One method that addresses this concern is infrared and visible image fusion. Its purpose is to generate an aggregate image which can granularly and systematically illustrate scene details in a range of lighting conditions. Our study introduces a novel approach to this method with marked improvements. We utilize non-subsampled shearlet transform (NSST) to obtain the low and high frequency sub-bands of infrared and visible imagery. For the low frequency sub-band fusion, we incorporate the local average… More >

Omar Fetitah¹, Ibrahim M. Almanjahie^2,3, Mohammed Kadi Attouch^1,*, Salah Khardani⁴

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2681-2694, 2021, DOI:10.32604/cmc.2021.015469

Abstract The problem of predicting continuous scalar outcomes from functional predictors has received high levels of interest in recent years in many fields, especially in the food industry. The k-nearest neighbor (k-NN) method of Near-Infrared Reflectance (NIR) analysis is practical, relatively easy to implement, and becoming one of the most popular methods for conducting food quality based on NIR data. The k-NN is often named k nearest neighbor classifier when it is used for classifying categorical variables, while it is called k-nearest neighbor regression when it is applied for predicting noncategorical variables. The objective of this paper is to use the… More >

Sung-Jung Hsiao¹, Wen-Tsai Sung^2,*

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 499-517, 2021, DOI:10.32604/iasc.2021.014911

Abstract The purpose of this research is to design an intelligent LED lighting control system with wireless remote control. Since the designed system is mainly based on Android applications, it controls wireless lighting modules through a sever by means of a smartphone, tablet computer, or another handheld mobile device, and the values displayed on the handheld device are used to monitor the establishment and design of the electricity state and multiple-LED light control scenarios in real time. The server is connected with a touch human-machine interface, digital meter, wireless lighting controller, infrared learning module, and other devices through RS-232 and RS-485… More >

Sung-Jung Hsiao¹, Wen-Tsai Sung^2,*

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 359-377, 2021, DOI:10.32604/iasc.2021.014905

Abstract Traditional agriculture has to face different climatic factors, resulting in unstable crop yields, whereas a plant factory is indoors, thus avoiding different natural disasters and insect pests. It is also available for bulk production in all-weather all year-round, guaranteeing crop quality. This study uses a wireless sensor network (WSN) architecture for multi-monitoring of a plant environment, aiming to improve its growing environment quality. In terms of monitoring environment, the sensor modules at the end device nodes are combined with Arduino for capturing the sensor values, which are transmitted by wireless signal transmission. The data of wireless signals are further transmitted… More >

Jingming Xia¹, Yi Lu¹, Ling Tan^2,*, Ping Jiang³

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 613-624, 2021, DOI:10.32604/cmc.2021.013457

Abstract Multi-source information can be obtained through the fusion of infrared images and visible light images, which have the characteristics of complementary information. However, the existing acquisition methods of fusion images have disadvantages such as blurred edges, low contrast, and loss of details. Based on convolution sparse representation and improved pulse-coupled neural network this paper proposes an image fusion algorithm that decompose the source images into high-frequency and low-frequency subbands by non-subsampled Shearlet Transform (NSST). Furthermore, the low-frequency subbands were fused by convolutional sparse representation (CSR), and the high-frequency subbands were fused by an improved pulse coupled neural network (IPCNN) algorithm,… More >