Pseudo Zernike Moments (PZMs) are very popular moments among the family of orthogonal radial moments. While several methods have been proposed to enhance accuracy, accurate PZMs computation for gray level images is still an open issue. PZMs suffer from image discretization error, geometric error and numerical integration error, which result in the degradation of the reconstructed images for high order of moments. It is observed that these errors are significant for the small images. In this paper, PZMs are computed after image interpolation on the small size images. Bi-cubic interpolation is used to increase the number of sampling points of the image. Experimental results show that the proposed method provides much improved accuracy of PZMs...
Various types of moments have been used to recognize image patterns in a number of applications. The...
The Zernike moments are calculated for a sample of scanned images of digits, generating a set of poi...
The efficiency of using Zernike moments when working with digital images obtained in the infrared re...
Pseudo-Zernike moments have better feature representation capabilities and are more robust to image ...
International audienceA new set, to our knowledge, of orthogonal moment functions for describing ima...
Zernike moments are complex moments with the orthogonal Zernike polynomials as kernel function, comp...
Zernike moments have many desirable properties, such as rotation invariance, robustness to noise, ex...
Abstract. Zernike Moments are useful tools in pattern recognition and image analysis due to their or...
This paper presents a novel approach to the fast computation of Zernike moments from a digital image...
Several pattern recognition applications use orthogonal moments to capture independent shape charac...
Abstract − Several pattern recognition applications use orthogonal moments to capture independent sh...
Aims/ objectives: To demontrate effectiveness of Zernike Moments for Image Classification. Zernike m...
Zernike moments are widely used in several pattern recognition applications, as invariant descriptor...
Zernike moments are widely used in several pattern recognition applications, as invariant descriptor...
Usually magnitude coefficients of some selected orders of ZMs and PZMs have been used as invariant i...
Various types of moments have been used to recognize image patterns in a number of applications. The...
The Zernike moments are calculated for a sample of scanned images of digits, generating a set of poi...
The efficiency of using Zernike moments when working with digital images obtained in the infrared re...
Pseudo-Zernike moments have better feature representation capabilities and are more robust to image ...
International audienceA new set, to our knowledge, of orthogonal moment functions for describing ima...
Zernike moments are complex moments with the orthogonal Zernike polynomials as kernel function, comp...
Zernike moments have many desirable properties, such as rotation invariance, robustness to noise, ex...
Abstract. Zernike Moments are useful tools in pattern recognition and image analysis due to their or...
This paper presents a novel approach to the fast computation of Zernike moments from a digital image...
Several pattern recognition applications use orthogonal moments to capture independent shape charac...
Abstract − Several pattern recognition applications use orthogonal moments to capture independent sh...
Aims/ objectives: To demontrate effectiveness of Zernike Moments for Image Classification. Zernike m...
Zernike moments are widely used in several pattern recognition applications, as invariant descriptor...
Zernike moments are widely used in several pattern recognition applications, as invariant descriptor...
Usually magnitude coefficients of some selected orders of ZMs and PZMs have been used as invariant i...
Various types of moments have been used to recognize image patterns in a number of applications. The...
The Zernike moments are calculated for a sample of scanned images of digits, generating a set of poi...
The efficiency of using Zernike moments when working with digital images obtained in the infrared re...