**About the Editor**

**Amelia Carolina Sparavigna** is a physics researcher, working mainly in the field of condensed matter physics and image processing. She graduated from the University of Torino in 1982 and obtained a Ph. D. in Physics at Politecnico di Torino in 1990. Since 1993, she has carried out teaching and research activities at the Politecnico. Her scientific researches cover the fields of thermal transport and Boltzmann equation, liquid crystals, and the related image processing of polarized light microscopy. She has proposed new methods of image processing inspired by physical quantities, such as coherence lengths. Her recent works mainly concern the problem of image segmentation. She is also interested in the history of physics and science. The papers that she has published in international journals are mainly on the topics of phonon thermal transport, the elastic theory of nematic liquid crystals, and the texture transitions of liquid crystals, investigated by means of image processing.

#### **Preface to "Entropy in Image Analysis III"**

Image analysis basically refers to any extraction of information from images, including those contained in large and complex datasets, such as the collections used for biometric identification or the sets of satellite surveys employed in the monitoring of Earth's climate changes. Image analysis is also necessary when providing methods for hiding information. When images play a major role in data transmission, it is imperative to protect them. Therefore, increasingly sophisticated algorithms, supported by artificial intelligence methods, are indispensable in the encryption and decryption of images, as they are up-to-date with their secure transmission. In addition to the extraction and encryption of information, another task for image analysis is related to the computer vision, where there are many applications that can only be properly managed using computers. These assorted scenarios tell us that "image analysis" is not just what we can imagine by taking our human vision system as a model; it is all the bulk of methods that computers use at present and the body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. In fact, the articles published in this book evidence that encryption and decryption, neural networks and machine learning are the leitmotifs of advanced image analysis. The gues<sup>t</sup> editor hopes that the readers can receive, from the published articles, fruitful hints and inspiration for future research and publications, for which the Topical Collection "Entropy in Image Analysis" could provide a proper publication place.

> **Amelia Carolina Sparavigna** *Editor*
