To represent the large amount of data in the biometric images an efficient feature extraction method is needed. Further biometric image acquisition is subject to deforming processes such as rotation, translation and scaling. Hence it is also required that the image representation be invariant to the deformations and sustain the discriminating features. Considering the trade off between the disc...

Content Based Image Retrieval (CBIR) systems based on shape using invariant image moments, viz., Moment Invariants (MI) and Zernike Moments (ZM) are available in the literature. MI and ZM are good at representing the shape features of an image. However, non-orthogonality of MI and poor reconstruction of ZM restrict their application in CBIR. Therefore, an efficient and orthogonal moment based C...

Zernike polynomials are a well known set of functions that find many applications in image or pattern characterization because they allow to construct shape descriptors that are invariant against translations, rotations or scale changes. The concepts behind them can be extended to higher dimension spaces, making them also fit to describe volumetric data. They have been less used than their prop...

In this paper, an algorithm is proposed for the classification of malignancy in mammogram. The types of malignancy can be classified as circumscribed, speculated, architectural distortion, miscellaneous, asymmetry and calcification. Chebyshev moments (CM), being discrete, are capable to combat the discritisation errors as compared to Zernike Moments (ZM), which are continuous moments. It is als...

Pseudo Zernike Moments (PZMs) are very popular moments among the family of orthogonal radial moments. While several methods have been proposed to enhance accuracy, accurate PZMs computation for gray level images is still an open issue. PZMs suffer from image discretization error, geometric error and numerical integration error, which result in the degradation of the reconstructed images for hig...

Article history: Received 21 June 2014 Received in revised form 7 April 2015 Accepted 11 April 2015 Available online 21 April 2015

Watermarking is an effective technology that solves many problems within a digitization project. A high capacity data entrenching scheme based on precise and fast framework for the computation of Zernike moments (ZMs) is proposed in this paper. The high capacity is achieved by maximizing data entrenching size and improving the hiding ratio after dipping the inaccuracies in the computation of ZM...