WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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2017 - 20192

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Author: search.filters.author.Ergün, Aslı

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  • Conference Object
    Registration and Optimization in Fintropic Graphs Using Branch Skeleton Features
    (Institute of Electrical and Electronics Engineers Inc., 2017) Ergün, Aslı; Ünlü, Mehmet Zübeyir; Ergün, Serkan; Ünlü, Mehmet Zübeyir; Güngör, Cengiz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    In image registration process, it is necessary to find the similarity of the images and thetranslation, rotation and scaling transformation parameter values that maximize the similarity between the two images. When the similarity measure and related parameters are calculated, information theory based entropic graphs can be used. In this study, similarity and optimization measures are compared on different entropic graphs. It has been seen that skeleton branch feature points to build entropic graphs give successful results.
  • Article
    A Saliency-Weighted Orthogonal Regression-Based Similarity Measure for Entropic Graphs
    (Springer, 2019) Ergün, Aslı; Ünlü, Mehmet Zübeyir; Ünlü, Mehmet Zübeyir; Güngör, Cengiz; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    Various measures are used to determine similarity ratios among images before and after image registration. Image registration methods are based on finding the translation, rotation, and scaling parameters that maximize the similarity between two images by taking advantage of the feature points and densities that are found. While the similarity criterion is calculated, it is possible and advantageous to use approximation methods on the graphs based on information theory. The current study proposes a new similarity measure based on saliency-weighted orthogonal regression derived from the weighted sums of the saliency map of the orthogonal regression residuals formed on the entropic graph. It is evaluated in terms of both quantitative and qualitative methods and compared with other graph-based similarity measures.