**4.4 The analysis of Loggia Mathia to Corvin Castle, Hunedoara**

Loggia Mathia includes few murals currently damaged. The primary interest is to perform the image analysis at this point in order to obtain the current status of

**Figure 16.** *Three metopes from Tropaeum Traiani Monuments.*

*Advanced Methods and New Materials for Cultural Heritage Preservation*

The histogram of illumination reveals the following:

*4.2.2 Structural analysis of the detail*

**Figure 15**, right-side picture).

• A slight increase in the average value from 0.4327 to 0.4718. The maximum value is at the illumination value of 0.4666, while for the entire image, it is about 0.3000. Therefore, the detail area has brightness above the average of the whole picture.

• The distribution is more uniform and with a high degree of symmetry around

The detail area of painting, as shown in **Figure 10**, was selected in order to exemplify

a local specific structural analysis. Detailed structural analysis of detail can provide essential information for evaluators and restorers. The chosen detail in this case is relevant because it contains a variety of colors and irregular shapes in relation to the whole image. Determining a structural pattern for the studied picture detail is done by analyzing the forms by passing the methodological steps enunciated in the first case study. By applying the image processing tools and the evaluation of the forms, the elements necessary for calculating the shape indicators are successively obtained.

**Figure 15** shows successively the result of image conversion in black-and-white, extracting regions with a filter for the area of detected regions and determining the center of gravity of the objects thus filtered (see red dot markings on the right). It is noted that the algorithm used light information to convert the image to black-and-white using an index value (intensity) threshold. The middle image in **Figure 15** shows the conversion result with the threshold automatically calculated by the algorithm based on average light. The white parts of the image correspond to pixels whose intensity exceeded the required threshold, so a considerable number of regions were detected. At this stage, we could decide either to raise the intensity threshold to reduce the number of regions by keeping the brightest or to apply an extra filter to one of the shape measures, for example, the area. Applying the second option to Area\_object > 200 has led to considerable reduction of regions and retaining more significant shapes, which are actually the largest and brightest pixel regions connected (see

Nondestructive methods of this type are effective in internationally recognized restoration and conservation analysis. We have chosen to apply them to art and archeology components that are part of the cultural heritage of Romania, are in a degree of advanced deterioration, and are threatened with extinction and for which any other method would not be efficient, in the field of fingerprint, authentication. For a more complete overview on the discussed methods, we extended the analysis with other two examples including metopes from Roman metopes to Tropaeum

the mean, approximating to a large extent the Gaussian curve.

**48**

**Figure 15.**

*Successive steps in region detection.*

#### *Advanced Methods and New Materials for Cultural Heritage Preservation*

the artifact. Then, the data will be used to perform comparative analysis with older images with significantly better quality. The most relevant analysis in this case is chromatics. The original image and the color-labeled regions are presented in **Figure 21**.

The chromatic analysis presented in **Figure 22** reveals the predominance of the red component in RGB spaces of the warm hues in perceptual space. No pure color was detected in the current fresco, but the histogram of the saturation shows a relatively high level of color blending with white. This is explained by the fact that painting is degraded by fading. The luminance of the image has the same distribution as R component which confirms the preponderant visual perception of this component. The color-labeled regions highlight the connected areas of pixels with same color in current images.

**Figure 17.**

*Chromatic components compared.*

**51**

**Figure 21.**

*A fresco of Loggia Mathia.*

**Figure 19.**

**Figure 20.**

*Metop 3: pattern detected.*

*Metop 2: pattern detected.*

*Intelligent Image Processing and Optical Means for Archeological Artifacts Examination*

*DOI: http://dx.doi.org/10.5772/intechopen.80615*

**Figure 18.** *Metop 1: pattern detected.*

*Intelligent Image Processing and Optical Means for Archeological Artifacts Examination DOI: http://dx.doi.org/10.5772/intechopen.80615*

**Figure 19.** *Metop 2: pattern detected.*

*Advanced Methods and New Materials for Cultural Heritage Preservation*

same color in current images.

the artifact. Then, the data will be used to perform comparative analysis with older images with significantly better quality. The most relevant analysis in this case is chromatics. The original image and the color-labeled regions are presented in **Figure 21**. The chromatic analysis presented in **Figure 22** reveals the predominance of the red component in RGB spaces of the warm hues in perceptual space. No pure color was detected in the current fresco, but the histogram of the saturation shows a relatively high level of color blending with white. This is explained by the fact that painting is degraded by fading. The luminance of the image has the same distribution as R component which confirms the preponderant visual perception of this component. The color-labeled regions highlight the connected areas of pixels with

**50**

**Figure 18.**

*Metop 1: pattern detected.*

**Figure 17.**

*Chromatic components compared.*

**Figure 20.** *Metop 3: pattern detected.*

**Figure 21.** *A fresco of Loggia Mathia.*

**Figure 22.** *Histograms in RGB and HSV color spaces.*

#### **5. Discussions**

The methods discussed above and the examples presented show the applicative potential of image processing techniques in arts, archeology, identity, and cultural heritage conservation. The primary objective of artifact investigation is, in fact, to get the most complete picture of them. Whether it is intended to authenticate the artifact or restoration—preserving it, the structural and chromatic details of the piece are essential for making the decision. The two presented case studies and related examples deal with two categories of artifacts: archeological pieces as threedimensional objects, respectively, and visual artworks on planar support. In the chosen examples, we have shown that the use of image processing models reveals interesting aspects and peculiarities regarding the chromatic composition and the structure of specific shapes and details. Moreover, formal image analysis tools provide numerical data (indicators) that can be integrated into information structures useful in the authentication, restoration, and conservation of artifacts.

The experiment in the first case study "Tablet from Tărtăria" is based on a picture taken from open sources about which we only know the resolution. The piece itself is a rough disc shape as a flatted calotte with a height (maximum thickness) of less than 1 cm. Its surface is etched with distinctive signs (ancient writing) and generally has local unevenness and rugoses specific to ceramic material. The perceived chromaticity is in the area of yellowish-reddish hues, which is also confirmed by the histogram. Evaluation of the chromatic composition across the image revealed an irregular color distribution (RGB), while detail analysis shows histograms with more concentrated and more regular distributions, close to the Gaussian form. The effect of uniform illumination at the moment of image capture is defining the quality of chromatic distribution.

For archeological artifacts, the chromatic pattern is generally due to alteration/ modification of the piece over time. However, the acquisition of images and the evaluation of chromatic components at the time of discovery, at the time of exposure to the museum, and periodically at different time intervals are important for the artifact record. In this way, useful databases can be compiled for the assessment of counterfeiting and the study of changes over time, an important aspect of conservation-restoration work. Formal analysis is equally important for completing the artifact datasheet. The "Tablet from Tărtăria" examined presents essential details in the form of engraved signs. Due to the spatial shape of the piece, it is impossible to detect all the signs by processing a single frontal image. The main states are the deformed projection of inclined or curved surfaces and the effect of uneven illumination. Also, some peculiarities of archeological pieces such as stamps, engravings or bas-reliefs, and even embroidery require a differential analysis on the normal image and the complementary image. As was seen in the analysis of the shape of the engravings, it was necessary to use the complementary black-and-white image. Complex threedimensional shapes marked by ornamental details characteristic of archeological

**53**

*Intelligent Image Processing and Optical Means for Archeological Artifacts Examination*

calibrated equipment for optical and photometric determinations.

compared to the original image (see **Figures 10** and **12a–c**).

the execution of some elements by applying clues, for example.

tion that helps restorers to reproduce faithfully.

composition as possible.

including chromatic parameters and/or shape properties (see **Table 2**).

artifacts generally impose certain limitations and special conditions when examining them based on images. However, shape analysis can provide trusted data for the artifact records if it is extracted from detailed images taken from the right angles with an optimal lighting scenario. All these conditions must be reproducible on stands with

In the case of flat surface artifacts such as canvas paintings, wall murals, floor mosaics or flat walls, upholstery, or other plain graphic artworks, image processing is very effective. The method is cost-effective, provides a lot of information, is not invasive or destructive to the artifact examined, and therefore is recommended to

Image analysis on Claude Monet's "Water Lilies and Japanese Bridge" highlights the relevance of the method for painting works. The chromatic analysis has more relevant details that contribute to the uniqueness of the work and possible to identify the Monet style. The overall appreciation is that the image is balanced in terms of color composition. This is distinguished by the intelligible visual aspect of the component images in both the basic color system and the perceptual system as

Compared to the analysis of "Tablet from Tartaria," we find a significant difference in the perceptual space regarding the hue and saturation components. While the archeological artifacts of ceramics have a specific natural color, undifferentiated in the nuances, and saturation planes, Monet's painting contains a shade treasure and reveals an elaborate technique of using colors mixed with white. Histograms in the perceptual color space provide identification data relevant to the "Water Lilies and Japanese Bridge" work, and in the case of the analyzed image detail, the general chromatic characteristics are preserved and in particular highlight the specificity of

The analysis of the shapes exemplified in the detail in "Water Lilies and Japanese Bridge" reveals the ability of the method to locate distinct regions in the image on a multi-criteria basis. The criterion used by us is "enlightenment and area" that selects all regions in the analyzed image that are brighter than a given threshold and larger than a prescribed value. Practically, any combination of criteria can be formed

The results from *Roman metopes to Tropaeum Traiani Monuments* show data specific to the stone artifacts in color space analyzed. Possible chromatic particularities may be caused by maneuvering or restoring cleaning itself. The shape analysis uses binary image and the color-labeled image in order to obtain information on topology of the artifact. The structural pattern of a metop includes geometrical informa-

The fresco from *Loggia Mathia to Corvin Castle, Hunedoara*, is a challenge for restoration. Because the painting is erased, i.e., blurry, the original chromaticity has been severely damaged, and at the same time, some elements of composition have been totally or partially lost. The color-based labeling helps to estimate the original shapes that were painted with the same color. Finally, the restorers have to use the comparative study to choose the colors and to restore the original

The extracted forms can be distinguished by their numerical measures (position, area, orientation, etc.) for the whole painting or its areas. Thus, the structuralchromatic pattern of artifacts in the category of graphical representations on planar support can be constituted by image and shape analysis. Image capture is also important for these artifacts, and great attention has to be paid to lighting. In the case of flat surface objects, there are no theoretical reasons for shading, but reflective and light scattering effects that compromise any image analysis may occur. Consequently, images must be captured at a resolution of at least 1,000,000 pixels

*DOI: http://dx.doi.org/10.5772/intechopen.80615*

do it before any other method of analysis.

#### *Intelligent Image Processing and Optical Means for Archeological Artifacts Examination DOI: http://dx.doi.org/10.5772/intechopen.80615*

artifacts generally impose certain limitations and special conditions when examining them based on images. However, shape analysis can provide trusted data for the artifact records if it is extracted from detailed images taken from the right angles with an optimal lighting scenario. All these conditions must be reproducible on stands with calibrated equipment for optical and photometric determinations.

In the case of flat surface artifacts such as canvas paintings, wall murals, floor mosaics or flat walls, upholstery, or other plain graphic artworks, image processing is very effective. The method is cost-effective, provides a lot of information, is not invasive or destructive to the artifact examined, and therefore is recommended to do it before any other method of analysis.

Image analysis on Claude Monet's "Water Lilies and Japanese Bridge" highlights the relevance of the method for painting works. The chromatic analysis has more relevant details that contribute to the uniqueness of the work and possible to identify the Monet style. The overall appreciation is that the image is balanced in terms of color composition. This is distinguished by the intelligible visual aspect of the component images in both the basic color system and the perceptual system as compared to the original image (see **Figures 10** and **12a–c**).

Compared to the analysis of "Tablet from Tartaria," we find a significant difference in the perceptual space regarding the hue and saturation components. While the archeological artifacts of ceramics have a specific natural color, undifferentiated in the nuances, and saturation planes, Monet's painting contains a shade treasure and reveals an elaborate technique of using colors mixed with white. Histograms in the perceptual color space provide identification data relevant to the "Water Lilies and Japanese Bridge" work, and in the case of the analyzed image detail, the general chromatic characteristics are preserved and in particular highlight the specificity of the execution of some elements by applying clues, for example.

The analysis of the shapes exemplified in the detail in "Water Lilies and Japanese Bridge" reveals the ability of the method to locate distinct regions in the image on a multi-criteria basis. The criterion used by us is "enlightenment and area" that selects all regions in the analyzed image that are brighter than a given threshold and larger than a prescribed value. Practically, any combination of criteria can be formed including chromatic parameters and/or shape properties (see **Table 2**).

The results from *Roman metopes to Tropaeum Traiani Monuments* show data specific to the stone artifacts in color space analyzed. Possible chromatic particularities may be caused by maneuvering or restoring cleaning itself. The shape analysis uses binary image and the color-labeled image in order to obtain information on topology of the artifact. The structural pattern of a metop includes geometrical information that helps restorers to reproduce faithfully.

The fresco from *Loggia Mathia to Corvin Castle, Hunedoara*, is a challenge for restoration. Because the painting is erased, i.e., blurry, the original chromaticity has been severely damaged, and at the same time, some elements of composition have been totally or partially lost. The color-based labeling helps to estimate the original shapes that were painted with the same color. Finally, the restorers have to use the comparative study to choose the colors and to restore the original composition as possible.

The extracted forms can be distinguished by their numerical measures (position, area, orientation, etc.) for the whole painting or its areas. Thus, the structuralchromatic pattern of artifacts in the category of graphical representations on planar support can be constituted by image and shape analysis. Image capture is also important for these artifacts, and great attention has to be paid to lighting. In the case of flat surface objects, there are no theoretical reasons for shading, but reflective and light scattering effects that compromise any image analysis may occur. Consequently, images must be captured at a resolution of at least 1,000,000 pixels

*Advanced Methods and New Materials for Cultural Heritage Preservation*

The methods discussed above and the examples presented show the applicative potential of image processing techniques in arts, archeology, identity, and cultural heritage conservation. The primary objective of artifact investigation is, in fact, to get the most complete picture of them. Whether it is intended to authenticate the artifact or restoration—preserving it, the structural and chromatic details of the piece are essential for making the decision. The two presented case studies and related examples deal with two categories of artifacts: archeological pieces as threedimensional objects, respectively, and visual artworks on planar support. In the chosen examples, we have shown that the use of image processing models reveals interesting aspects and peculiarities regarding the chromatic composition and the structure of specific shapes and details. Moreover, formal image analysis tools provide numerical data (indicators) that can be integrated into information structures

The experiment in the first case study "Tablet from Tărtăria" is based on a picture taken from open sources about which we only know the resolution. The piece itself is a rough disc shape as a flatted calotte with a height (maximum thickness) of less than 1 cm. Its surface is etched with distinctive signs (ancient writing) and generally has local unevenness and rugoses specific to ceramic material. The perceived chromaticity is in the area of yellowish-reddish hues, which is also confirmed by the histogram. Evaluation of the chromatic composition across the image revealed an irregular color distribution (RGB), while detail analysis shows histograms with more concentrated and more regular distributions, close to the Gaussian form. The effect of uniform illumination at the moment of image capture is defining the quality of chromatic distribution. For archeological artifacts, the chromatic pattern is generally due to alteration/ modification of the piece over time. However, the acquisition of images and the evaluation of chromatic components at the time of discovery, at the time of exposure to the museum, and periodically at different time intervals are important for the artifact record. In this way, useful databases can be compiled for the assessment of counterfeiting and the study of changes over time, an important aspect of conservation-restoration work. Formal analysis is equally important for completing the artifact datasheet. The "Tablet from Tărtăria" examined presents essential details in the form of engraved signs. Due to the spatial shape of the piece, it is impossible to detect all the signs by processing a single frontal image. The main states are the deformed projection of inclined or curved surfaces and the effect of uneven illumination. Also, some peculiarities of archeological pieces such as stamps, engravings or bas-reliefs, and even embroidery require a differential analysis on the normal image and the complementary image. As was seen in the analysis of the shape of the engravings, it was necessary to use the complementary black-and-white image. Complex threedimensional shapes marked by ornamental details characteristic of archeological

useful in the authentication, restoration, and conservation of artifacts.

**52**

**5. Discussions**

*Histograms in RGB and HSV color spaces.*

**Figure 22.**

in natural light conditions or near natural light sources, in the absence of concentrated and directional sources that cause reflections and diffuses on the surface of the artifact.
