Computer science—especially pattern recognition, signal processing and mathematical algorithms—can offer important information about archaeological finds, information that is otherwise undetectable by the human senses and traditional archaeological approaches. Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology offers state of the art research in computational pattern recognition and digital archaeometry. Computer science researchers in pattern recognition and machine intelligence will find innovative research methodologies combined to create novel and efficient computational systems, offering robust, exact, and reliable performance and results. Archaeologists, conservators, and historians will discover reliable automated methods for quickly reconstructing archaeological materials and benefit from the application of non-destructive, automated processing of archaeological finds.

About the Author

Constantin Papaodysseus received the Diploma degree in electrical and computer engineering from the National Technical University of Athens (NTUA) and the MSc degree from Manchester University, United Kingdom. He received the PhD degree in computer engineering from NTUA. From 1996 - 2000, he was an assistant professor at NTUA in the Department of Electrical and Computer Engineering. Since 2001, he has been an associate professor in the same department at NTUA. His research interests include image processing, pattern recognition, biomedical engineering, music and sound processing and automatic recognition, applications of computer science to archaeology, applied mathematics, algorithm robustness and quantization error analysis, adaptive algorithms, etc. He has more than 50 publications in international journals on these subjects.

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