کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
461857 696638 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A lossless copyright authentication scheme based on Bessel–Fourier moment and extreme learning machine in curvature-feature domain
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
A lossless copyright authentication scheme based on Bessel–Fourier moment and extreme learning machine in curvature-feature domain
چکیده انگلیسی

To overcome some drawbacks existing in current zero-watermarking methods, a lossless copyright authentication scheme is proposed in this paper. This scheme designs a multiple zero-watermarking algorithm based on Bessel–Fourier moment and extreme learning machine (ELM) in curvature-feature domain, develops a method for image feature enhancement and noise suppression in curvature-feature domain, and presents a simple algorithm which uses Bessel–Fourier moment phase to estimate the rotation angle of the rotation-attacked image. The experimental results, involving five types of images, indicate the proposed scheme has better overall performance compared to other five current methods, especially in the aspects of resisting high ratio cropping and large angle rotation attacks. Finally, some related factors including phase and magnitude components, feature vector dimension and ELM optimization are considered in the algorithm performance evaluation.


► Develop a method for image feature enhancement and noise suppression.
► Present a simple rotation estimation algorithm for the rotation-attacked image.
► The proposed scheme has the better overall performance than the five current methods.
► The proposed scheme can resist high ratio cropping and large angle rotation attacks.
► Some related factors are considered in the algorithm performance evaluation.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems and Software - Volume 86, Issue 1, January 2013, Pages 222–232
نویسندگان
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