In this paper a novel general methodology is introduced for the computer-aided reconstruction of the magnificent wall-paintings of the Greek island Thera (Santorini), painted in the middle of the second millennium BC. These wall-paintings are excavated in fragments and, as a result, their reconstruction is a painstaking and a time-consuming process. Therefore, in order to facilitate and speed up this process a proper system has been developed based on the introduced methodology. According to this methodology each fragment is photographed, its picture is introduced to the computer, its contour is obtained and subsequently all fragments contours are compared in a manner proposed herein. Both the system and the methodology presented here, extract the maximum possible information from the contour shape of fragments of an arbitrary initially unbroken plane object, to point out possible fragments matching. This methodology has been applied to two excavated fragmented wall-paintings consisting of 262 fragments, with full success but most important it has been used to reconstruct, for the first time, unpublished wall-paintings parts from a set of 936 fragments. 2 A. INTRODUCTION-PROBLEM DESCRIPTIONThe discovery of the wall-paintings at Akrotiri of the Greek island Thera (Santorini), is of outstanding importance for human knowledge of the early Aegean world and not only. According to prominent archaeologists these wall-paintings rank alongside the greatest archaeological discoveries.The late professor Marinatos originated the excavations, which are now successfully continued by Professor Christos Doumas. As with the treasures of Pompeii and Herculaneum, the wall-paintings of Thera were preserved due to the seal of the pumice from the great eruption of a volcano [1]. As a rule, the walls decorated with paintings no longer survive. They collapsed together with their painted coat before the volcanic eruption, due to particularly strong earthquakes. Thus, a single painting is usually scattered into many fragments mixed with the fragments of other wall-paintings, too. The restoration of the wall-paintings from the fragments is a very painstaking and time consuming process frequently demanding many months or even years of dedicated, experienced personnel work for a single wallpainting restoration. Therefore, the development of a system that will contribute to the automatic restoration of these wall-paintings is of fundamental importance for this archaeological research, but for many others too, which face the problem of an image reconstruction from excavated fragments.Each excavated wall-painting fragment after being cleaned, is being photographed with a very strict protocol, so that very similar illumination conditions, a fixed distance of the fragment plane from the camera focus and minimal photo distortion are ensured. Subsequently, the obtained image is processed and eventually each photographed fragment is embedded into a white background frame, which we call the absolute frame of reference of the specific fragmen...

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Abstract-In this paper, a methodology of general applicability is presented for answering the question if an artist used a number of archetypes to draw a painting or if he drew it freehand. In fact, the contour line parts of the drawn objects that potentially correspond to archetypes are initially spotted. Subsequently, the exact form of these archetypes and their appearance throughout the painting is determined. The method has been applied to celebrated Thera Late Bronze Age wall paintings with full success. It has been demonstrated that the artist or group of artists has used seven geometrical archetypes and seven corresponding well-constructed stencils (four hyperbolae, two ellipses, and one Archimedes' spiral) to draw the wall painting "Gathering of Crocus" in 1650 B.C. This method of drawing seems to be unique in the history of arts and of great importance for archaeology, and the history of mathematics and sciences, as well.Index Terms-Image line pattern analysis, archaeological image edge analysis, archaeological object reconstruction, curve fitting, statistical pattern matching.

Abstract-In this paper, a new methodology is presented for the automated recognition-identification of musical recordings that have suffered from a high degree of playing speed and frequency band distortion. The procedure of recognition is essentially based on the comparison between an unknown musical recording and a set of model ones, according to some predefined specific characteristics of the signals. In order to extract these characteristics from a musical recording, novel feature extraction algorithms are employed. This procedure is applied to the whole set of model musical recordings, thus creating a model characteristic database. Each time we want an unknown musical recording to be identified, the same procedure is applied to it, and subsequently, the derived characteristics are compared with the database contents via an introduced set of criteria. The proposed methodology led to the development of a system whose performance was extensively tested with various types of broadcasted musical recordings. The system performed successful recognition for the 94% of the tested recordings. It should be noted that the presented system is parallelizable and can operate in real time.Index Terms-Automatic music recognition, distorted in frequency recordings, fuzzy logic and music, musical recording automated recognition, music pattern recognition, music processing.

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In this paper, an original general methodology is introduced to establish whether a handmade shape corresponds to a given geometrical prototype. Using this methodology, one can decide if an artist had the intention of drawing a specific mathematical prototype or not. This analysis is applied to the 1650 B.C. wall paintings from the prehistoric settlement on Thera, and inferences of great archaeological and historical importance are made. In particular, strong evidence is obtained suggesting that the spirals depicted on the wall paintings correspond to linear (Archimedes) spirals, certain shapes correspond to canonical 48-gon and 32-gon, while other shapes correspond to parts of ellipses. It seems that the presented wall paintings constitute the earliest archaeological findings on which these geometrical patterns appear with such remarkable accuracy.

In this paper, a novel methodology is introduced for the identification of the workmen (hands) that carved ancient inscriptions. This methodology employs specific geometric characteristics of each letter and computes the mean value and variance of these characteristics for each one of the available inscriptions separately. Subsequently, we define original decision thresholds that make use of the statistical distribution of the difference of these values in order to attribute an inscription to a given hand. The inscriptions of the hands under consideration have been properly processed and all information extracted, both visual and statistical, is stored in a suitable database. Application of this methodology to nine Athenian inscriptions, some of which contain very similar letters, offered correct, clear-cut hand identification.