Extensive testing shows that the audio Zernike moments in lower orders are very robust to common signal processing operations, such as MP3 compression, low-pass filtering, etc. Based on the observations, in this paper, a robust watermark scheme is proposed by embedding the bits into the low-order moments. By analyzing and deducting the linear relationship between the audio amplitude and moments...

A method using Zernike Moments and Histogram of Oriented Gradients for classification of plant leaf images is proposed in this paper. After preprocessing, we compute the shape features of a leaf using Zernike Moments and texture features using Histogram of Oriented Gradients and then the Support Vector Machine classifier is used for plant leaf image classification and recognition. Experimental ...

This paper proposes a robust and effective shape feature, which is based on a set of orthogonal complex moments of images known as Zernike moments. Zernike moment phase is usually not used in image description since it’s sensitive to image rotations. However, phase captures important image information, which is revealed by our numerical analysis of image reconstruction. We therefore propose com...

The increasing interest in processing sequences of images motivates development of techniques for sequence-based object analysis and description. Accordingly, new velocity moments have been developed to allow a statistical description of both shape and associated motion through an image sequence. Through a generic framework motion information is determined using the established centralised mome...

A robust and geometric invariant digital image watermarking scheme based on feature extraction and local Zernike transform is proposed in this paper. The Adaptive Harris Detector is proposed to extract feature patches for watermarking use. A local Zernike moments-based watermarking scheme is raised, where the watermarked patches can be obtained directly by inverse Zernike Transform. Each extrac...

− Several pattern recognition applications use orthogonal moments to capture independent shape characteristics of an image, with minimum amount of information redundancy in a feature set. Legendre, Zernike, and Pseudo-Zernike moments are examples of such orthogonal feature descriptors. An image can also be reconstructed from a sufficiently large number of orthogonal moments. Discrete orthogonal...

A robust and geometric invariant digital image watermarking scheme based on feature extraction and local Zernike transform is proposed in this paper. The Adaptive Harris Detector is proposed to extract feature patches for watermarking use. A local Zernike moments-based watermarking scheme is raised, where the watermarked patches can be obtained directly by inverse Zernike Transform. Each extrac...

Shape identification and feature extraction are the main concern of any pattern recognition system. Object parameters are mostly dependent on spatio-temporal relationships among the pixels. However feature extraction is a complex phenomenon which needs to be addressed from the invariance property, irrespective of position and orientation. Zernike moments are used as shape descriptors and identi...

Classification of heterogeneous classes present in the Hyperspectral image is one of the recent research issues in the field of remote sensing. This work presents a novel technique that classifies Hyperspectral images that contain number of classes by making use of the image moments. Recently, researchers have introduced a number of neural network models and structured output based methods for ...

Palmprint verification is an approach for verifying a palmprint input by matching the input to the claimed identity template stored in a database. If the dissimilarity measure between the input and the claimed template is below the predefined threshold value, the palmprint input is verified possessing same identity as the claimed identity template. This paper introduces an experimental evaluati...