We studied the application of the Pseudo-Zernike features as image parameters (instead of the Hillas parameters) for the discrimination between the images produced by atmospheric electromagnetic showers caused by gamma-rays and the ones produced by atmospheric electromagnetic showers caused by hadrons in the MAGIC Experiment. We used a Support Vector Machine as classification algorithm with the...

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

In image watermarking, the watermark’s vulnerability to geometric transformations has long been a difficult problem. Using invariant image features to carry the watermark is an effective approach to addressing this problem. In this paper, a multibit geometrically robust image watermarking algorithm using Zernike moments (ZMs) and pseudo-Zernike moments (PZMs) is proposed. Unlike its counterpart...

Structural genomics initiatives have started to accumulate protein structures of unknown function in an increasing pace. Conventional sequence-based function prediction methods are not able to provide useful function information to most of such structures. Thus, structure-based approaches have been developed, which predict function of proteins by capturing structural characteristics of function...

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...

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...