This book comprises a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2021), held at Technical University of Sofia, Sofia, Bulgaria, during 0810 July 2021. The book covers research papers in the field of N-dimensional multicomponent image processing, multidimensional image representation and super-resolution, 3D image processing and reconstruction, MD computer vision systems, multidimensional multimedia systems, neural networks for MD image processing, data-based MD image retrieval and knowledge data mining, watermarking, hiding and encryption of MD images, MD image processing in robot systems, tensor-based data processing, 3D and multi-view visualization, forensic analysis systems for MD images and many more.

Presents research works in the field of multidimensional signal processing Gathers the outcomes of the NAMSP 2021, held in Sofia, Bulgaria, during July 2021 Offers a reference guide for researchers and practitioners in academia and industry

Autorentext

Professor Roumen Kountchev, Ph.D., D. Sc. is a professor at the Faculty of Telecommunications, Dept. of Radio Communications and Video Technologies, Technical University of Sofia, Bulgaria. Areas of interest include digital signal and image processing, image compression, multimedia watermarking, video communications, pattern recognition, and neural networks. Professor Kountchev has 350 papers published in magazines and proceedings of conferences; 20 books; 47 book chapters; 21 patents. He had been principle investigator of 38 research projects. At present, he is a member of Euro Mediterranean Academy of Arts and Sciences and president of Bulgarian Association for Pattern Recognition (member of Intern. Association for Pattern Recognition). He is the editorial board member of: Intern. J. of Reasoning-based Intelligent Systems; Intern. J. Broad Research in Artificial Intelligence and Neuroscience; KES Focus Group on Intelligent Decision Technologies; Egyptian Computer Science J.; Intern. J. of Bio-Medical Informatics and e-Health, and Intern. J. Intelligent Decision Technologies. He has been a plenary speaker at: WSEAS Intern. Conf. on Signal Processing, 2009, Istanbul, Turkey; WSEAS Intern. Conf. on Signal Processing, Robotics and Automation, University of Cambridge 2010, UK; WSEAS Intern. Conf. on Signal Processing, Computational Geometry and Artificial Vision 2012, Istanbul, Turkey; Intern. Workshop on Bioinformatics, Medical Informatics and e-Health 2013, Ain Shams University, Cairo, Egypt; Workshop SCCIBOV 2015, Djillali Liabes University, Sidi Bel Abbes, Algeria; Intern. Conf. on Information Technology 2015 and 2017, Al Zayatoonah University, Amman, Jordan; WSEAS European Conf. of Computer Science 2016, Rome, Italy; The 9th Intern. Conf. on Circuits, Systems and Signals, London, UK, 2017; IEEE Intern. Conf. on High Technology for Sustainable Development 2018 and 2019, Sofia, Bulgaria; The 8th Intern. Congress of Information and Communication Technology, Xiamen, China, 2018; general chair of the Intern. Workshop New Approaches for Multidimensional Signal Processing, July 2020, Sofia, Bulgaria. Professor Rumen Mironov, Technical University of Sofia, Sofia, Bulgaria, Dr. Rumen Mironov received his MSc and PhD in Telecommunications from Technical University of Sofia and MSc in Applied Mathematics and Informatics from Faculty of Applied Mathematics and Informatics. He is currently the head of the Department of Radio Communications and Video Technologies, Technical University of Sofia, Bulgaria. His current research focuses on digital signal and image processing, pattern recognition, audio and video communications, information systems, computer graphics, and programming languages. He is a member of Bulgarian Association of Pattern Recognition (IAPR) and Bulgarian Union of Automation and Automation Systems. Rumen Mironov is the author of more than 60 scientific publications. Professor Kazumi Nakamatsu, University of Hyogo, Kobe, Japan, Kazumi Nakamatsu received the Ms. Eng. and Dr. Sci. from Shizuoka University and Kyushu University, Japan, respectively. His research interests encompass various kinds of logic and their applications to Computer Science, especially paraconsistent annotated logic programs and their applications. He has developed some paraconsistent annotated logic programs called Annotated Logic Program with Strong Negation (), Vector ALPSN (VALPSN), Extended VALPSN (EVALPSN), and before-after EVALPSN (bf-EVALPSN) recently and applied them to various intelligent systems such as a safety verification-based railway interlocking control system and process order control. He is an author of over 150 papers, 20 book chapters, and 10 edited books published by prominent publishers. Kazumi Nakamatsu has chaired various international conferences, workshops, and invited sessions, and he has been a member of numerous international program committees of workshops and conferences in the area of Computer Science. He has served as the editor-in-chief of the International Journal of Reasoning-based Intelligent Systems (IJRIS), and he is now the founding editor of IJRIS and an editorial board member of many international journals. He has contributed numerous invited lectures at international workshops, conferences, and academic organizations. He also is a recipient of numerous research paper awards. He is a member of ACM.

Inhalt
Masked Face Detection using Artificial Intelligent Techniques.- Object Motion Detection in Video by Fusion of RPCA and NMF Decompositions.- Hierarchical Decomposition of Third-order Tensor trough Adaptive Branched Inverse Difference Pyramid Based on 3D-WHT.- Multimodal Technique for Human Authentication using Fusion of Palm and Dorsal Hand Veins.- SIFT based Feature Matching Algorithm for Cartoon Plagiarism Detection.- Image Recognition Technology Based Evaluation Index of Ship Navigation Risk in Bridge Area.- Equalization of Directional Multidimensional Histograms of Matrix and Tensor Images.- Small Object Detection of Remote Sensing Images Based on Residual Branch of Feature Fusion.- Meta-Learning with Logistic Regression for Multi-Classification.- Measurement for Blade Edge Based on Machine Vision.