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Beijing Chen
Researcher at Nanjing University of Information Science and Technology
Publications - 65
Citations - 2396
Beijing Chen is an academic researcher from Nanjing University of Information Science and Technology. The author has contributed to research in topics: Color image & Quaternion. The author has an hindex of 24, co-authored 59 publications receiving 1818 citations. Previous affiliations of Beijing Chen include New Jersey Institute of Technology & Sungkyunkwan University.
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Journal ArticleDOI
Color Image Analysis by Quaternion-Type Moments
TL;DR: This paper provides a general formula of QTMs from which a set of quaternion-valued QTM invariants (QTMIs) are derived to image rotation, scale and translation transformations by eliminating the influence of transformation parameters.
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Robust color image watermarking technique in the spatial domain
Qingtang Su,Beijing Chen +1 more
TL;DR: The experimental results show that the proposed watermarking algorithm can obtain better invisibility of watermark and stronger robustness for common attacks, e.g., JPEG compression, cropping, and adding noise.
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Quaternion Zernike moments and their invariants for color image analysis and object recognition
Beijing Chen,Huazhong Shu,Hua Zhang,G. Chen,Christine Toumoulin,Jean-Louis Dillenseger,Limin Luo +6 more
TL;DR: It is shown that the QZMs can be obtained from the conventional Zernike moments of each channel, and the theoretical framework to construct a set of combined invariants with respect to rotation, scaling and translation (RST) transformation is provided.
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Effective and Efficient Image Copy Detection with Resistance to Arbitrary Rotation
TL;DR: A novel effective and efficient image copy detection method is proposed based on two global features extracted from rotation invariant partitions, which can effectively and efficiently resist rotations with arbitrary degrees.
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Full 4-D quaternion discrete Fourier transform based watermarking for color images
TL;DR: The theoretical analysis and experimental results show that these algorithms offer better performance in terms of capacity and robustness to most common attacks, including JPEG compression, noise, cropping and filtering and so on, than other QDFT based algorithms for the same watermarked image quality.