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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 47294 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Marvasti, Farrokh; Amini, Arash
- Abstract:
- Considering the tremendous development in imaging systems’ industry, today we can afford to have imaging equipment, capable of taking multispectral images in very high resolution. One of the remarkable benefits of this technology is in the realm of arts and particularly in museums. Taking advantage of the potentials of multispectral, highquality imaging, curators will be able to probe their priceless works of art ( e.g. paintings ) without putting them in danger through invasive research. Besides, one can investigate and control the transformation of these works through time by using this new imaging method. Recently, Multispectral Imaging of paintings, in different frequency bands from approximately 300 nm to 1000 nm, has been proposed and used in some museums. Since these images are taken with different filters from visible light to infra-red, one might expect that they contain some data beyond what is seen in visible light images. So these images contain data from beneath layers of the paintings, which can be compared with the RGB image and result in extracting early sketches of the painter which are the basis of those paintings. In this project the ultimate goal is to find and extract those regions from multispectral bands that cannot be seen in the RGB image. We use statistical methods and image processing tools in order to extract those hidden objects automatically by computer. The process will start with using a statistical tool known as canonical correlation analysis to find a projection which uncorrelates the frequency bands from 3 RGB bands. Then we can use canny edge detector to find edges in the resulting image bands from previous section and in the RGB file. After that we can implement some morphological operations to reduce redundant edges that represent data which can also be found in the RGB file, or some noisy edges. At the end we implement an algorithm to find edges that can be linked together to represent a larger object and connect them using active contours. Results show that this approach can be helpful in finding hidden layers of the paintings which is a stepping stone to find the method of painters in their paintings
- Keywords:
- Image Processing ; Active Contour Model ; Multispectral Image ; Canonical Height ; Painting ; Canonical Correlation Analysis ; Morphological Operation
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