Mosaicking of torn image using graph algorithm and color pixel matching
Mosaicking of torn image is a challenge for the investigators while reconstructing image from nonlinear torn images. Numerous researches were conducted in the past few decades to develop accurate algorithms to reconstruct images from torn image. Due to several factors, torn image reconstruction is n...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/50727/25/IbrahimThorigMFC2014.pdf |
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| Summary: | Mosaicking of torn image is a challenge for the investigators while reconstructing image from nonlinear torn images. Numerous researches were conducted in the past few decades to develop accurate algorithms to reconstruct images from torn image. Due to several factors, torn image reconstruction is not matured. In past researches, researchers focused on only image contour matching. The challenge in the contour matching technique is that extracting exact contour of the image fragment. Therefore, in this project, a new technique has been proposed to address the torn image reconstruction based on contour matching and contour pixel color matching. This project discussed the existing techniques used for torn image reconstruction and the advantages and disadvantages of those techniques. In this study, the proposed solution was evaluated based on the performance of the system in terms of accuracy and computational speed of the image reconstruction. The simulation indicates that the proposed technique performs better than existing technique in terms of accuracy. While simulating the system, 15 images were fragmented out of which 60% of the images were reconstructed fully, 33.33% of images reconstructed ¾ of the image fragments and 6.7% of images reconstructed half of the image. Most surprisingly, none of the images failed to reconstruct, at least 50% of image fragments reconstructed in the worst reconstruction while performing simulations. In terms of computational speed, it takes unacceptable time to reconstruct which is worse than traditional methods. Therefore, researcher classified the area’s to refine which will be helpful for the future researchers, those who are attentive in the field of image reconstruction field. |
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