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Data mining approach to Image feature extraction in old painting restoration

Gancarczyk J., Sobczyk J.

Foundations of Computing and Decision Sciences

2013

Vol. 38, No. 3

159--174

In this paper a new approach to image segmentation was discussed. A model based on a data mining algorithm set on a pixel level of an image was introduced and implemented to solve the task of identification of craquelure and retouch traces in digital images of artworks. Both craquelure and retouch identification are important steps in art restoration process. Since the main goal is to classify and understand the cause of damage, as well as to forecast its further enlargement, a proper tool for a precise detection of the damaged area is needed. However, the complex nature of the pattern is a reason why a simple, universal detection algorithm is not always possible to be implemented. Algorithms presented in this work apply mining structures which depend of expandable set of attributes forming a feature vector, and thus offer an elastic structure for analysis. The result obtained by our method in craquelure segmentation was improved comparing to the results achieved by mathematical morphology methods, which was confirmed by a qualitative analysis.

Nieinwazyjne badania obiektów zabytkowych z wykorzystaniem fotografii w świetle widzialnym, fluorescencji UV i reflektografii IR

Gancarczyk J., Gancarczyk T.

Pomiary Automatyka Kontrola

2010

R. 56, nr 3

268-271

Nieinwazyjne badania obiektów zabytkowych oparte na komputerowym przetwarzaniu i analizie obrazu zajmują coraz bardziej znaczącą pozycję pośród znanych do tej pory podobnych badań w innych dziedzinach, jak medycyna, analiza zdjęć satelitarnych, wojskowość czy kontrola jakości w przemyśle. Niniejsza praca przedstawia przegląd literatury dotyczącej poruszanego tematu a także opis badań własnych przeprowadzonych na udostępnionym obiekcie muzealnym. Przedstawione zostało stanowisko do wykonania zdjęcia w świetle widzialnym, zasady poprawnego oświetlenia obiektu oraz przykład zastosowania makrofotografii. Dodatkowo zaprezentowano otrzymane wyniki analizy z wykorzystaniem fluorescencji UV (ultrafiolet) i reflektografii IR (podczerwień) oraz ich interpretację.

Non-invasive inspection of museum objects based on computer image processing and analysis has recently gained a signifying position among other similar methods known so far in medicine, satellite image analysis, military or quality control in the industry. Investigation outside the visible light spectrum is a basic tool to reveal underdrawings as well as to recognize retouching and former restoration marks in the painting. Computer vision will not replace traditional art historical methods of connoisseurship but enhance and extend them. They can rely on visual features that are hard to determine by eye, for instance subtle relationships among the structure of a brushstroke at different scales or colours. This paper provides an overview of the literature and a case study concerning the analysis performed on a given museum object (Fig. 2, with courtesy of the Museum of Bielsko-Biała). The workplace for VIS photography is shown, as well as the schema of proper illumination of a painting (Fig. 3) and an example of use of macrophotography (Fig. 5, craquelure analysis). Additionally, there are presented the results of inspection with use of UV fluorescence (Fig. 7) and IR reflectography (Fig. 8) together with their interpretation.