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Mosaicking of torn image using graph algorithm and color pixel matching

机译:使用图算法和彩色像素匹配对残缺图像进行拼接

摘要

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
机译:从非线性撕裂图像重建图像时,撕裂图像的马赛克化是研究人员面临的挑战。在过去的几十年中进行了许多研究,以开发出准确的算法来从残缺图像中重建图像。由于多种因素,残缺图像重建尚未成熟。在过去的研究中,研究人员仅关注图像轮廓匹配。轮廓匹配技术的挑战在于提取图像片段的精确轮廓。因此,在该项目中,提出了一种新的技术来解决基于轮廓匹配和轮廓像素颜色匹配的残影重建。该项目讨论了用于残像重建的现有技术以及这些技术的优缺点。在这项研究中,基于系统的性能在图像重建的准确性和计算速度方面对提出的解决方案进行了评估。仿真表明,所提出的技术在准确性方面要优于现有技术。在模拟系统时,将15幅图像分割成碎片,其中60%的图像被完全重建,33.33%的图像重建了3/4图像片段,而6.7%的图像重建了一半图像。最令人惊讶的是,没有图像无法重建,至少有50%的图像片段在执行模拟时以最差的重建速度重建。在计算速度方面,重建花费了不可接受的时间,这比传统方法差。因此,研究人员对该区域进行了分类以进行改进,这将对将来的研究人员(在图像重建领域专心研究的人员)有所帮助

著录项

  • 作者

    Thorig Ibrahim;

  • 作者单位
  • 年度 2014
  • 总页数
  • 原文格式 PDF
  • 正文语种 en
  • 中图分类

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