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Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future.

Technology: general issues --- History of engineering & technology --- Newton-Raphson’s method --- chaos --- image encryption/decryption --- security analysis --- image encryption --- cryptanalysis --- hyper-chaotic --- ribonucleic acid --- color image encryption --- transformed Zigzag --- image segmentation --- computer-assisted diagnosis --- machine learning --- spleen injury detection --- hyperchaotic --- permutation --- diffusion --- multiple bit operation --- circular-step wedge --- contrast-detail --- mutual information --- visible ratio --- anode heel effect --- prior information --- entropy --- fwi --- regularization --- inverse problems --- bat optimization --- human crowd behavior (HCB) --- improved entropy (IE) --- Jaccard similarity --- multi-person counting --- particles gradient motion (PGM) --- speeded up robust features (SURF) --- Retinex --- image enhancement --- gamma correction --- low-light image --- HSV color space --- scan route --- Hilbert curve --- run-length-based entropy coding --- image and video compression --- secure communication --- cellular neural network --- power-divergence measure --- computed tomography --- iterative reconstruction --- maximum-likelihood expectation-maximization method --- continuous-time image reconstruction --- n/a --- Newton-Raphson's method

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Image analysis is a fundamental task for extracting information from images acquired across a range of different devices. Since reliable quantitative results are requested, image analysis requires highly sophisticated numerical and analytical methods—particularly for applications in medicine, security, and remote sensing, where the results of the processing may consist of vitally important data. The contributions to this book provide a good overview of the most important demands and solutions concerning this research area. In particular, the reader will find image analysis applied for feature extraction, encryption and decryption of data, color segmentation, and in the support new technologies. In all the contributions, entropy plays a pivotal role.

keyframes --- time-delay --- whale optimization algorithm --- multilevel thresholding --- multi-exposure image fusion --- additive manufacturing --- patch structure decomposition --- ultra-sound images --- 3D scanning --- Arimoto entropy --- contrast enhancement --- spatial filling factor --- depth maps --- image processing --- 3D prints --- differential evolution --- field of experts --- normalized divergence measure --- image privacy --- multiscale top-hat transform --- q-exponential --- texture information entropy --- diffusion --- hybrid algorithm --- Weibull statistics --- adaptive selection --- nonextensive entropy --- computer aided diagnostics --- fatty liver --- random forest --- DNA encoding --- low contrast --- entropy --- Minkowski island --- fuzzy entropy --- free-form deformations --- person re-identification --- chaotic system --- DNA computing --- pavement --- information entropy --- discrete entropy --- Tsallis statistics --- video skimming --- prime-indexed primes --- natural scene statistics (NSS) --- Hénon map --- q-sigmoid --- image entropy --- Shannon entropy --- macrotexture --- Shannon’s entropy --- binary image --- multi-feature fusion --- image analysis --- uncertainty assessment --- non-rigid registration --- hash layer --- Cantor set --- dynamic filtering --- deep neural network --- security analysis --- multiple-image encryption --- Hamming distance --- blind image quality assessment (BIQA) --- q-Gaussian --- remote sensing --- decay trend --- chaotic cryptography --- chaotic strategy --- cross-entropy loss --- random insertion --- metabolic syndrome --- sign languages --- generalized entropies --- relevance feedback --- image retrieval --- two-dimensional chaotic economic map --- cryptanalysis --- infrared images --- 3D Latin cube --- SHA-256 hash value --- gradient distributions --- structural entropy --- discrete cosine transform (DCT) --- chaotic map --- hepatic steatosis --- machine vision --- electromagnetic field optimization --- security --- image segmentation --- quantization loss --- colonoscopy --- video summarization --- permutation --- Kapur’s entropy --- surface quality assessment --- permutation-diffusion --- Ramanujan primes --- Rényi entropies --- chosen-plaintext attack --- image encryption --- dynamic index --- color image segmentation --- ultrasound --- Otsu method --- sigmoid --- reconstruction --- image information entropy --- 3-D digital imaging --- positron emission tomography --- medical imaging

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Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens.

star image --- image denoising --- reinforcement learning --- maximum likelihood estimation --- mixed Poisson–Gaussian likelihood --- machine learning-based classification --- non-uniform foundation --- stochastic analysis --- vehicle–pavement–foundation interaction --- forest growing stem volume --- coniferous plantations --- variable selection --- texture feature --- random forest --- red-edge band --- on-shelf availability --- semi-supervised learning --- deep learning --- image classification --- machine learning --- explainable artificial intelligence --- wildfire --- risk assessment --- Naïve bayes --- transmission-line corridors --- image encryption --- compressive sensing --- plaintext related --- chaotic system --- convolutional neural network --- color prior model --- object detection --- piston error detection --- segmented telescope --- BP artificial neural network --- modulation transfer function --- computer vision --- intelligent vehicles --- extrinsic camera calibration --- structure from motion --- convex optimization --- temperature estimation --- BLDC --- electric machine protection --- touchscreen --- capacitive --- display --- SNR --- stylus --- laser cutting --- quality monitoring --- artificial neural network --- burr formation --- cut interruption --- fiber laser --- semi-supervised --- fuzzy --- noisy --- real-world --- plankton --- marine --- activity recognition --- wearable sensors --- imbalanced activities --- sampling methods --- path planning --- Q-learning --- neural network --- YOLO algorithm --- robot arm --- target reaching --- obstacle avoidance

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Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas.

History of engineering & technology --- image binarization --- optical character recognition --- local entropy filter --- thresholding --- image preprocessing --- image entropy --- image encryption --- medical color images --- RGB --- chaotic system --- crowd behavior analysis --- salient crowd motion detection --- repulsive force --- direction entropy --- node strength --- Pompe disease --- children --- quantitative muscle ultrasound --- texture-feature parametric imaging --- compound chaotic system --- S-box --- image information entropy --- image chaotic encryption --- cryptography --- Latin cube --- bit cube --- chosen plaintext attack --- atmosphere background --- engine flame --- infrared radiation --- detectability --- image quality evaluation --- image retrieval --- pooling method --- convolutional neural network --- feature distribution entropy --- lossless compression --- pattern classification --- machine learning --- malaria infection --- entropy --- Golomb–Rice codes --- image processing --- image segmentation --- weld segmentation --- weld evaluation --- convolution neural network --- Python --- Keras --- RSNNS --- MXNet --- brain-computer interface (BCI) --- electroencephalography (EEG) --- motor imagery (MI) --- continuous wavelet transform (CWT) --- convolutional neural network (CNN) --- hyperchaotic system --- filtering --- DNA computing --- diffusion --- deep neural network --- data expansion --- blind image quality assessment --- saliency and distortion --- human visual system --- declining quality --- data hiding --- AMBTC --- steganography --- stego image --- dictionary-based coding --- pixel value adjusting --- neuroaesthetics --- symmetry --- balance --- complexity --- chiaroscuro --- normalized entropy --- renaissance --- portrait paintings --- art history --- art statistics --- chaotic systems --- DNA coding --- security analysis --- magnetic resonance images --- non-maximum suppression --- object detection --- key-point detection --- IoU --- feature fusion --- quasi-resonant Rossby/drift wave triads --- Mordell elliptic curve --- pseudo-random numbers --- substitution box --- nuclear spin generator --- medical image --- peak signal-to-noise ratio --- key space calculation --- Duchenne muscular dystrophy --- ultrasound --- backscattered signals --- medical imaging --- neural engineering --- computer vision --- crowd motion detection --- security

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Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens.

Technology: general issues --- History of engineering & technology --- star image --- image denoising --- reinforcement learning --- maximum likelihood estimation --- mixed Poisson–Gaussian likelihood --- machine learning-based classification --- non-uniform foundation --- stochastic analysis --- vehicle–pavement–foundation interaction --- forest growing stem volume --- coniferous plantations --- variable selection --- texture feature --- random forest --- red-edge band --- on-shelf availability --- semi-supervised learning --- deep learning --- image classification --- machine learning --- explainable artificial intelligence --- wildfire --- risk assessment --- Naïve bayes --- transmission-line corridors --- image encryption --- compressive sensing --- plaintext related --- chaotic system --- convolutional neural network --- color prior model --- object detection --- piston error detection --- segmented telescope --- BP artificial neural network --- modulation transfer function --- computer vision --- intelligent vehicles --- extrinsic camera calibration --- structure from motion --- convex optimization --- temperature estimation --- BLDC --- electric machine protection --- touchscreen --- capacitive --- display --- SNR --- stylus --- laser cutting --- quality monitoring --- artificial neural network --- burr formation --- cut interruption --- fiber laser --- semi-supervised --- fuzzy --- noisy --- real-world --- plankton --- marine --- activity recognition --- wearable sensors --- imbalanced activities --- sampling methods --- path planning --- Q-learning --- neural network --- YOLO algorithm --- robot arm --- target reaching --- obstacle avoidance