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...

most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. to solve the problem, this paper utilizes zernike moment (zm) and pseudo zernike moment (pzm) to extract object contour features in all situations such as rotation, scaling and shifting of object i...

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...

This paper presents an invariant image watermarking scheme by introducing the Polar Harmonic Transform (PHT), which is a recently developed orthogonal moment method. Similar to Zernike moment (ZM) and pseudo-Zernike moment (PZM) approaches, PHT is defined on a circular domain. The magnitudes of PHTs are invariant to image rotation and scaling. Furthermore, the PHTs are free of numerical instabi...

Mild cognitive impairment (MCI) conversion prediction is a vital challenge in the area of Alzheimer’s disease (AD) as it could determine possible treatment pathways for AD patients. In this work, we presented robust MCI framework based on 3D-Zernike Moment (3D-ZM) method that generates statistical features (e.g., shape, texture, and symmetry information) from 3D-MRI scans improved dynamic parti...

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...

Invariant features play an essential role in many pattern recognition applications due to their robustness to different environmental settings. In this research, two of the invariant moments, the Zernike Moment (ZM) and the Legendre Moment (LM), have been investigated for their suitability and computational efficiency in Arabic letter recognition. This paper starts with an introduction on Arabi...

Despite the fact that images are a primary source of information, the rapid growing of tools that used to amendment images makes the reliability of the digital images in risk. Copy-Move forgery is one important method to forge an image; where part of the image is copied and pasted in another part of the same image. Regarding the related literature in this topic, many methods were developed to d...

In the paper, a new recognition method for logos imaged by mobile phone cameras is presented which can be incorporated with mobile phone services for use in enterprise identification, corporate website access, traffic sign reading, security check, content awareness, and the related applications. The main challenge in applying the logo recognition for mobile phone applications is the inevitable ...

Most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. To solve the problem, this paper utilizes Zernike Moment (ZM) and Pseudo Zernike Moment (PZM) to extract object contour features in all situations such as rotation, scaling and shifting of object i...