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access icon free Robust image hashing via colour vector angles and discrete wavelet transform

© The Institution of Engineering and Technology
Received 24/01/2013, Accepted 27/07/2013, Revised 01/07/2013, Published 21/10/2013

Colour vector angle has been widely used in edge detection and image retrieval, but its investigation in image hashing is still limited. In this study, the authors investigate the use of colour vector angle in image hashing and propose a robust hashing algorithm combining colour vector angles with discrete wavelet transform (DWT). Specifically, the input image is firstly resized to a normalised size by bi-cubic interpolation and blurred by a Gaussian low-pass filter. Colour vector angles are then calculated and divided into non-overlapping blocks. Next, block means of colour vector angles are extracted to form a feature matrix, which is further compressed by DWT. Image hash is finally formed by those DWT coefficients in the LL sub-band. Experiments show that the proposed hashing is robust against normal digital operations, such as JPEG compression, watermarking embedding and rotation within 5°. Receiver operating characteristics curve comparisons are conducted and the results show that the proposed hashing is better than some well-known algorithms.

Inspec keywords: image watermarking; image colour analysis; cryptography; image coding; interpolation; discrete wavelet transforms; matrix algebra; low-pass filters; Gaussian processes

Other keywords: LL subband; watermarking embedding; receiver operating characteristic curve; Gaussian low-pass filter; DWT; JPEG compression; nonoverlapping blocks; feature matrix; bicubic interpolation; discrete wavelet transform; robust image hashing; colour vector angle

Subjects: Other topics in statistics; Integral transforms; Cryptography; Algebra; Filtering methods in signal processing; Interpolation and function approximation (numerical analysis); Other topics in statistics; Interpolation and function approximation (numerical analysis); Integral transforms; Computer vision and image processing techniques; Algebra; Image and video coding

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