Abstract
We consider a classifier based on Independent Component Analysis Mixture Modelling (ICAMM) to model the feature joint-probability density. This classifier is applied to a challenging novel application: classification of archaeological ceramics. ICAMM gathers relevant characteristics that have general interest for material classification. It can deal with arbitrary forms of the underlying probability densities in the feature vector space as nonparametric methods can do. Mutual dependences among the features are modelled in a parametric form so that ICAMM can achieve good performance even with a training set of relatively small size, which is characteristic of parametric methods. Moreover, in the training stage, ICAMM can incorporate probabilistic semisupervision (PSS): labelling by an expert of a portion of the whole available training set of samples. These properties of ICAMM are well-suited for the problem considered: classification of ceramic pieces coming from four different periods, namely, Bronze Age, Iberian, Roman, and Middle Ages. A feature set is obtained from the processing of the ultrasonic signal that is recorded in through-transmission mode using an ad hoc device. A physical explanation of the results is obtained with comparison with classical methods used in archaeology. The results obtained demonstrate the promising potential of ICAMM for material classification.
Highlights
Determining the historical period of archaeological ceramic shards is important for many archaeological applications, to reconstruct human activities of the past
The ceramic pieces were measured using a device where the ceramic piece is placed between two cases that adjust to the curved surfaces of the piece
We have presented the results of applying Independent Component Analysis Mixture Modelling (ICAMM) to a challenging application in the area of nondestructive testing of materials: the classification of archaeological ceramic pieces into different historic periods
Summary
Determining the historical period of archaeological ceramic shards is important for many archaeological applications, to reconstruct human activities of the past. The standardization of an efficient and nondestructive testing (NDT) method for ceramic characterization could become an important contribution for archaeologists. We consider a method to sort archaeological ceramic shards based on ultrasonic nondestructive evaluation. This method aims to be economic, fast, precise, and innocuous for the ceramic pieces. It consists of three steps: measuring by the through-transmission technique, extracting features from the measured ultrasonic signals, and classifying the feature set in classes corresponding to historic or protohistoric periods
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