Image hashing maps an image to a short binary sequence representing the image’s characteristics. This paper proposes a new image hashing method using Zernike moments that are an effective means for extracting robust features from an image. The method is based on rotation invariance of magnitudes and corrected phases of Zernike moments. Similarity between hashes is measured with the Hamming dist...

Hand-gesture recognition presents a challenging problem for computer vision due to the articulated structure of the human hand and the complexity of the environments in which it is typically applied. Solving such a problem requires a robust tracking mechanism which in turn depends on an effective feature descriptor and classifier. Moment invariants, as discriminative feature descriptors, have b...

In this paper, the quaternion Bessel-Fourier moments are introduced. The significance of phase information in quaternion Bessel-Fourier moments is investigated and an accurate estimation method for rotation angle is described. Furthermore, a new set of invariant descriptors based on the magnitude and the phase information of quaternion Bessel-Fourier moments is derived. Experimental results sho...

The aim of image steganalysis is to detect the presence of hidden messages in stego images. We propose a blind image steganalysis method in Contourlet domain and then show that the embedding process changes statistics of Contourlet coefficients. The suspicious image is transformed into Contourlet space, and then the statistics of Contourlet subbands coefficients are extracted as features. We us...

In this paper, we give a detailed analysis of the accuracy of Zernike moments in terms of their discretization errors and the reconstruction power. It is found that there is an inherent limitation in the precision of computing the Zernike moments due to the geometric nature of a circular domain. This is explained by relating the accuracy issue to a celebrated problem in analytic number theory o...

Even if lots of object invariant descriptors have been proposed in the literature, putting them into practice in order to obtain a robust system face to several perturbations is still a studied problem. Comparative studies between the most commonly used descriptors put into obviousness the invariance of Zernike moments for simple geometric transformations and their ability to discriminate objec...

An exact analysis of the numerical errors being generated during the computation of the Zernike moments, by using the well-known ‘q-recursive’ method, is attempted in this paper. Overflow is one kind of error, which may occur when one needs to calculate the Zernike moments up to a high order. Moreover, by applying a novel methodology it is shown that there are specific formulas, which generate ...

Feature extraction is the key process in any pattern recognition issues. There is no exception in object recognition. In this paper, several feature extraction approaches in the field of object recognition are summed up. Zernike and Hu are two invariant moments and geodesic descriptors are applied directly to binary images and so we can have more information about the general shape of the objec...

Moments and moment invariants have become a powerful tool in pattern recognition and image analysis. Conventional methods to deal with color images are based on RGB decomposition or graying, which may lose some significant color information. In this paper, by using the algebra of quaternions, we introduce the quaternion Zernike moments (QZMs) to deal with the color images in a holistic manner. ...