Zernike moments are complex moments with the orthogonal Zernike polynomials as kernel function, compared with other moments; Zernike moments have greater advantages in image rotation and low noise sensitivity. Because of the Zernike moments have image rotation invariance, and can construct arbitrary high order moments, it can be used for target recognition. In this paper, the Zernike moment algorithm is improved, which makes it having scale invariance in the processing of digital image. At last, an application of the improved Zernike moments in image recognition is given
A number of Computer Vision and Artificial Intelligence applications are based on descriptors that a...
This paper presents a new class of Tchebichef moments in polar coordinate form, using which rotation...
This paper presents a new class of Tchebichef moments in polar coordinate form, using which rotation...
International audienceA new set, to our knowledge, of orthogonal moment functions for describing ima...
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...
Various types of moments have been used to recognize image patterns in a number of applications. The...
This paper presents a novel approach to the fast computation of Zernike moments from a digital image...
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...
The Zernike moment algorithm and R-Tree algorithm are known as state of the art in the recognition o...
There are lots of ways to perform object recognition. This paper is part of a project studying objec...
Pseudo-Zernike moments have better feature representation capabilities and are more robust to image ...
Several pattern recognition applications use orthogonal moments to capture independent shape charac...
A number of Computer Vision and Artificial Intelligence applications are based on descriptors that a...
This paper presents a new class of Tchebichef moments in polar coordinate form, using which rotation...
This paper presents a new class of Tchebichef moments in polar coordinate form, using which rotation...
International audienceA new set, to our knowledge, of orthogonal moment functions for describing ima...
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...
Various types of moments have been used to recognize image patterns in a number of applications. The...
This paper presents a novel approach to the fast computation of Zernike moments from a digital image...
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...
The Zernike moment algorithm and R-Tree algorithm are known as state of the art in the recognition o...
There are lots of ways to perform object recognition. This paper is part of a project studying objec...
Pseudo-Zernike moments have better feature representation capabilities and are more robust to image ...
Several pattern recognition applications use orthogonal moments to capture independent shape charac...
A number of Computer Vision and Artificial Intelligence applications are based on descriptors that a...
This paper presents a new class of Tchebichef moments in polar coordinate form, using which rotation...
This paper presents a new class of Tchebichef moments in polar coordinate form, using which rotation...