Old painting digital color restoration

Pappas, M.; Pitas, Ioannis

doi:10.1007/978-1-4471-1597-7_30

Cited by 7 publications

(6 citation statements)

References 1 publication

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“…Image processing (IP) techniques can be used for extracting information regarding the eroded areas in artworks, as indicated by previous works [6][7][8][9][10]. However, the investigation of such approaches is still in early stages.…”

Section: Introductionmentioning

confidence: 99%

Optical inspection for quantification of decay on stone surfaces

Kapsalas

Maravelaki-Kalaitzaki

Zervakis

et al. 2007

NDT & E International

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This paper examines a novel approach of corrosion damage analysis based on image processing for quantitative and qualitative evaluation of degradation effects on stone surfaces. This methodology can be applied in situ in association with a variety of nondestructive monitoring schemes, and on images acquired from several imaging modalities, capturing from micro-to macro-scale characteristics. Our analysis methodology was evaluated on three non-destructive monitoring techniques of cleaned and not cleaned stone surfaces, namely on digital camera, reflectography and fiber optic microscope images. Further to validating the potential of the various imaging modalities, the paper also assesses the corrosion rate and the efficiency of the recruited cleaning methods. The derived results are in accordance with chemical analyses revealing the deterioration patterns of the studied surfaces. r

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Section: Introductionmentioning

confidence: 99%

Optical inspection for quantification of decay on stone surfaces

Kapsalas

Maravelaki-Kalaitzaki

Zervakis

et al. 2007

NDT & E International

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“…[3][4][5] Image-based techniques have been recently used in order to interpret the optical characteristics of pigments in various areas of electromagnetic spectrum. Examples of cush use are, a system for automatic analysis of infrared reflectograms to determine the drawing tool used in painting, 6 visible reflectance spectophotometry used to evaluate potential pigment combination for inpainting, 7 multispectral image analysis and its application in art image classification.…”

Section: Introductionmentioning

confidence: 99%

A Bayesian decision model for watercolour analysis

2007

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Bayesian Classification methods can be applied to images of watercolour paintings in order to characterize blue and green pigments used in these paintings. Pigments found in watercolour paintings are semi-transparent materials and their analysis provides important information on the date, the painter, the place of the production of watercolour paintings and generally on the authenticity of these works of art. However, watercolour pigments are difficult to characterize because their intensity depends on the amount of liquid spread during painting and the reflective properties of the underlying support. The method describedin this paper is non-destructive, non invasive, does not involve sampling and can be applied in situ. The methodology is based on the photometric properties of pigments and produce computational models which classify diverse types of pigments found in watercolour paintings. These pigments are photographed in the visible and infrared area of electromagnetic spectrum and models based on statistical characteristics of intensity values using a mixture of Gaussian functions are created. Finally the pigments are classified using a Bayesian classification algorithm to process the generate models.

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“…Most of the image-based research in inks and pigments found in artifacts is focused in the generation rather than analysis and are mainly applied in the restoration of colors in paintings [15]. Alternatively research in machine vision is carried out in the analysis and modelling of color and mainly focuses on the visual retrieval of information in digital image libraries [8,14,16].…”

Section: Introductionmentioning

confidence: 99%

Probabilistic image-based characterization of manuscript inks

2005

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Inks constitute the main element in Medieval manuscripts and their examination and analysis provides an invaluable source of information on the authenticity of the manuscripts, the number of authors involved and dating of the manuscripts. Most existing methods for the analysis of ink materials are based on destructive testing techniques that require the physicochemical sampling of data. Such methods cannot be widely used because of the historical and cultural value of manuscripts. In this paper we present a novel approach for discriminating and identifying inks based on the correlations of image variations under visible and infrared illumination. Such variations are studied using co-occurrence matrices and detect the behavior of the inks during the scripting process.

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Old painting digital color restoration

Cited by 7 publications

References 1 publication

Optical inspection for quantification of decay on stone surfaces

Optical inspection for quantification of decay on stone surfaces

A Bayesian decision model for watercolour analysis

Probabilistic image-based characterization of manuscript inks

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