Static gestures can convey certain meanings and act as specific transitions in dynamic gestures. Therefore, recognizing static gestures is one of the most important aspects of gesture recognition. In this paper, a new approach is presented for recognizing static gestures based on Zernike moments (ZMs) and pseudo-Zernike moments (PZMs). The binary hand silhouette is first accommodated with a min...

Optical character recognition is undoubtedly considered as a one of the most active and dynamic fields of pattern recognition and artificial intelligence; it really provides in fact a solution for recognizing large volume of patterns automatically. The purpose of the present study is to compare in one hand between the performances of three novel hybrid methods used in OCR for extracting efficie...

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. ...

The explosive growth of image data leads to the research and development of image content searching and indexing systems. Image annotation systems aim at annotating automatically animage with some controlled keywords that can be used for indexing and retrieval of images. This paper presents a comparative evaluation of the image content annotation system by using the multilayer neural networks a...

The purpose of multi-frame super resolution (SR) is to combine multiple low resolution (LR) images to produce one high resolution (HR) image. The major challenge of classic SR approaches is accurate motion estimation between the frames. To address this problem, fuzzy motion estimation method has been proposed that replaces value of each pixel using the weighted average of all its neighboring pi...

An algorithm was proposed for very fast and low-complexity computation of three-dimensional Zernike moments. The 3D Zernike moments were expressed in terms of exact 3D geometric moments where the later are computed exactly through the mathematical integration of the monomial terms over the digital image/object voxels. A new symmetry-based method was proposed to compute 3D Zernikemoments with 87...

In this paper, we present a fingerprint matching approach based on localizing the matching regions in fingerprint images. The determination of the location of such Region Of Interest (ROI) using only the information related to core points based on a novel feature vectors extracted for each fingerprint image by Zernike Moment Invariant (ZMI) as the shape descriptor. The Zernike Moments is select...

Validation of computational solid mechanics simulations requires full-field comparison methodologies between numerical and experimental results. The continuous Zernike and Chebyshev moment descriptors are applied to decompose data obtained from numerical simulations and experimental measurements, in order to reduce the high amount of ‘raw’ data to a fairly modest number of features and facilita...

Face recognition is an interesting field of computer vision with many commercial and ‎scientific applications. It is considered as a very hot topic and challenging problem at the ‎moment. Many methods and techniques have been proposed and applied for this purpose, ‎such as neural networks, PCA, Gabor filtering, etc. Each approach has its weaknesses as ‎well as its points of strength. This paper...