Marco Perez Cisneros – författare

The use of metaheuristic algorithms (MA) has been increasing in recent years, and the image processing field is not the exempted of their application. In the last two years a big amount of MA has been introduced as alternatives for solving complex optimization problems. This book collects the most prominent MA of the 2019 and 2020 and verifies its use in image processing tasks. In addition, literature review of both MA and digital image processing is presented as part of the introductory information. Each algorithm is detailed explained with special focus in the tuning parameters and the proper implementation for the image processing tasks. Besides several examples permits to the reader explore and confirm the use of this kind of intelligent methods. Since image processing is widely used in different domains, this book considers different kinds of datasets that includes, magnetic resonance images, thermal images, agriculture images, among others. The reader then can have some ideas of implementation that complement the theory exposed of each optimization mechanism. Regarding the image processing problems this book consider the segmentation by using different metrics based on entropies or variances. In the same way, the identification of different shapes and the detection of objects are also covered in the corresponding chapters. Each chapter is complemented with a wide range of experiments and statistical analysis that permits the reader to judge about the performance of the MA. Finally, there is included a section that includes some discussion and conclusions. This section also provides some open questions and research opportunities for the audience.

The use of metaheuristic algorithms (MA) has been increasing in recent years, and the image processing field is not the exempted of their application. In the last two years a big amount of MA has been introduced as alternatives for solving complex optimization problems. This book collects the most prominent MA of the 2019 and 2020 and verifies its use in image processing tasks. In addition, literature review of both MA and digital image processing is presented as part of the introductory information. Each algorithm is detailed explained with special focus in the tuning parameters and the proper implementation for the image processing tasks. Besides several examples permits to the reader explore and confirm the use of this kind of intelligent methods. Since image processing is widely used in different domains, this book considers different kinds of datasets that includes, magnetic resonance images, thermal images, agriculture images, among others. The reader then can have some ideas of implementation that complement the theory exposed of each optimization mechanism. Regarding the image processing problems this book consider the segmentation by using different metrics based on entropies or variances. In the same way, the identification of different shapes and the detection of objects are also covered in the corresponding chapters. Each chapter is complemented with a wide range of experiments and statistical analysis that permits the reader to judge about the performance of the MA. Finally, there is included a section that includes some discussion and conclusions. This section also provides some open questions and research opportunities for the audience.

This book gathers a selection of papers presented at the 2018 International Conference on Software Process Improvement (CIMPS 2018). CIMPS 2018 offered a global forum for researchers and practitioners to present and discuss the latest innovations, trends, findings, experiences and concerns in Software Engineering, embracing several aspects such as Software Processes, Security in Information and Communication Technology, and Big Data. 

Two of the conference’s main aims were to support the drive toward a holistic symbiosis of the academic world, society, industry, government and business community, and to promote the creation of networks by disseminating the results of recent research in order to align their needs. CIMPS 2018 was made possible by the support of the CIMAT A.C., CUCEI (Universidad de Guadalajara, México), AISTI (Associação Ibérica de Sistemas e Tecnologas de Informação), and ReCIBE (Revista electrónica de Computación, Informática, Biomédica y Electrónica).

This book presents the use of efficientEvolutionary Computation (EC) algorithms for solving diverse real-world imageprocessing and pattern recognition problems. It provides an overview of thedifferent aspects of evolutionary methods in order to enable the reader inreaching a global understanding of the field and, in conducting studies onspecific evolutionary techniques that are related to applications in imageprocessing and pattern recognition. It explains the basic ideas of the proposedapplications in a way that can also be understood by readers outside of thefield. Image processing and pattern recognition practitioners who are notevolutionary computation researchers will appreciate the discussed techniquesbeyond simple theoretical tools since they have been adapted to solvesignificant problems that commonly arise on such areas. On the other hand,members of the evolutionary computation community can learn the way in whichimage processing and pattern recognition problems can be translated into anoptimization task. The book has been structured so that each chapter can beread independently from the others. It can serve as reference book for studentsand researchers with basic knowledge in image processing and EC methods.