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المؤلفFawad
المؤلفRahman, Muhibur
المؤلفKhan, Muhammad Jamil
المؤلفAsghar, Muhammad Adeel
المؤلفAmin, Yasar
المؤلفBadnava, Salman
المؤلفMirjavadi, Seyed Sajad
تاريخ الإتاحة2020-06-23T20:45:42Z
تاريخ النشر2019
اسم المنشورIEEE Access
المصدرScopus
الرقم المعياري الدولي للكتاب21693536
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/ACCESS.2019.2959326
معرّف المصادر الموحدhttp://hdl.handle.net/10576/15139
الملخصThis work introduces a novel local patch descriptor that remains invariant under varying conditions of orientation, viewpoint, scale, and illumination. The proposed descriptor incorporate polynomials of various degrees to approximate the local patch within the image. Before feature detection and approximation, the image micro-texture is eliminated through a guided image filter with the potential to preserve the edges of the objects. The rotation invariance is achieved by aligning the local patch around the Harris corner through the dominant orientation shift algorithm. Weighted threshold histogram equalization (WTHE) is employed to make the descriptor in-sensitive to illumination changes. The correlation coefficient is used instead of Euclidean distance to improve the matching accuracy. The proposed descriptor has been extensively evaluated on the Oxford's affine covariant regions dataset, and absolute and transition tilt dataset. The experimental results show that our proposed descriptor can categorize the feature with more distinctiveness in comparison to state-of-the-art descriptors. - 2013 IEEE.
راعي المشروعThis work was supported by the Qatar National Library.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعCovariant
descriptor
handcrafted feature
patch
textures
العنوانImage Local Features Description through Polynomial Approximation
النوعArticle
الصفحات183692-183705
رقم المجلد7
dc.accessType Open Access


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