22-12-2012, 04:31 PM
Detection and removal of cracks in digitized paintings
Detection and removal of cracks in digitized paintings.doc (Size: 1.43 MB / Downloads: 209)
INTRODUCTION
Many paintings, especially old ones, suffer from breaks in the substrate, the paint, or the varnish. These patterns are usually called cracks or craquelure and can be caused by aging, drying, and mechanical factors. Age cracks can result from no uniform contraction in the canvas or wood-panel support of the painting, which stresses the layers of the painting. Drying cracks are usually caused by the evaporation of volatile paint components and the consequent shrinkage of the paint. Finally, mechanical cracks result from painting deformations due to external causes, e.g., vibrations and impacts. The appearance of cracks on paintings deteriorates the perceived image quality.
However, one can use digital image processing techniques to detect and eliminate the cracks on digitized paintings. Such a “virtual” restoration can provide clues to art historians, museum curators and the general public on how the painting would look like in its initial state, i.e., without the cracks. Furthermore, it can be used as a nondestructive tool for the planning of the actual restoration. The user should manually select a point on each crack to be restored. Other research areas that are closely related to crack removal include image in painting which deals with the reconstruction of missing or damaged image areas by filling in information from the neighboring areas, and disocclusion, i.e., recovery of object parts that are hidden behind other objects within an image.
Methods developed in these areas assume that the regions where information has to be filled in are known The former are usually based on partial differential equations (PDEs) and on the calculus of variations whereas the latter rely on texture synthesis principles. A technique that decomposes the image to textured and structured areas and uses appropriate interpolation techniques depending on the area where the missing information lies has also been proposed. The results obtained by these techniques are very good. A methodology for the restoration of cracks on digitized paintings, which adapts and integrates a number of image processing and analysis tools is proposed in this paper.
MOTIVATION
This project is entitled as “Detection and removal of cracks in digitized paintings” .The main objective of the project is to remove and detect the cracks. Remove Cracks is the most important step in software development process. Before developing the tool it is necessary to determine the time factor, economy ,company strength. Once the tool the programmers need lot of external support.
PROBLEM DEFINITION
The Technique Consists Of The Following Stages:
• Crack Detection;
• Separation Of The Thin Dark Brush Strokes, Which Have Been
Misidentified As Cracks;
• Crack Filling (Interpolation).
It contain various modules included in the project as follows:
1. Input module
2. Gray scale conversion module
3. Cracks Detection module
4. Crack filling module
5. Output module
A certain degree of user interaction, most notably in the crack-detection stage, is required for optimal results. User interaction is rather unavoidable since the large variations observed in the typology of cracks would lead any fully automatic algorithm to failure. However, all processing steps can be executed in real time, and, thus, the user can instantly observe the effect of parameter tuning on the image under study and select in an intuitive way the values that achieve the optimal visual result. Needless to say, only subjective optimality criteria can be used in this case since no ground truth data are available. The opinion of restoration experts that inspected the virtually restored images was very positive.
OBJECTIVE OF THE PROJECT
The proposed system involves exact crack detection and filling procedure. It involves top-hat transformation, region-growing algorithm
(grassfire algorithm) and median filter procedures.
• Decomposes the image to textured and structured areas and uses appropriate interpolation techniques depending on the area where the missing information lies has also been proposed.
• The restoration of cracks on digitized paintings, which adapts and integrates a number of image processing and analysis tools is proposed.
• Crack detection and removal bears certain similarities with methods proposed for the detection and removal of scratches and other artifacts from motion picture.
LITERATURE SURVEY
Literature survey is the most important step in software development process. Before developing the tool it is necessary to determine the time factor, economy n company strength. Once the programmer start building the tool the programmers need lot of external support.
The appearance of cracks on paintings deteriorates the perceived image quality. However, one can use digital image processing techniques to detect and eliminate the cracks on digitized paintings. Such a “virtual” restoration can provide clues to art historians, museum curators and the general public on how the painting would look like in its initial state, i.e., without the cracks. Furthermore, it can be used as a nondestructive tool for the planning of the actual restoration. A system that is capable of tracking and interpolating cracks is presented in [1].
The user should manually select a point on each crack to be restored. A method for the detection of cracks using multi oriented Gabor filters is presented in [2].
Crack detection and removal bears certain similarities with methods proposed for the detection and removal of scratches and other artifacts from motion picture [3]–[5] However, such methods rely on information obtained over several adjacent frames for both artifact detection and filling and, thus, are not directly applicable in the case of painting cracks. Other research areas that are closely related to crack removal include image in painting which deals with the reconstruction of missing or damaged image areas by filling in information from the neighboring areas, and disocclusion, i.e., recovery of object parts that are hidden behind other objects within an image.
Methods developed in these areas assume that the regions where information has to be filled in are known. Different approaches for interpolating information in structured A possible solution would be to perform edge detection or segmentation on the image and confine the filling of cracks that cross edges or region borders to pixels from the corresponding region. Use of image inpainting techniques . A possible solution to this shortcoming would be to apply the crack detection algorithm locally on this area and select a low threshold value. Another situation where the system (more particularly, the crack filling stage) does not perform as efficiently as expected is in the case of cracks that cross the border between regions of different color.