Digital image reconstruction using Zernike moments

Author(s):  
Alfonso Padilla-Vivanco ◽  
Areli Martinez-Ramirez ◽  
Fermin-Solomon Granados-Agustin

Moments are set of values used to describe the information contained in the image. In this paper the content of the image is represented with the help of fast legendre moments. Legendre moments has the advantage that these moments are calculated exactly without any loss in information while other moments like geometric moments, zernike moments etc suffer from approximation errors and geometric error when applied to digital images. Legendre moments are also more suitable for image reconstruction. Experimental results show that the proposed system is very efficient in computing moments at much faster time than the Zernike moments since fast legendre moments calculates the moments as two ID function rather as a 2D function of a digital image and the results of reconstruction in case of tampering is also shown


2013 ◽  
Vol 62 (18) ◽  
pp. 1-5
Author(s):  
Md. IqbalQuraishi ◽  
Mallike De ◽  
Goutam Das ◽  
Abhishek Srivastav

2004 ◽  
Author(s):  
Alfonso Padilla-Vivanco ◽  
A. Colunga-Ruiz

2014 ◽  
Vol 21 (6) ◽  
pp. 682-686 ◽  
Author(s):  
Shekhar S. Chandra ◽  
Nicolas Normand ◽  
Andrew Kingston ◽  
Jeanpierre Guedon ◽  
Imants Svalbe

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Hongwei Zhao

In order to improve the training level of Sanda movement, this article uses an image analysis method to reconstruct the detailed characteristics of the movement and apply them to the actual training process. Since the traditional wavelet reconstruction method is affected by the accuracy of the decomposition scale, this paper proposes an improved method of Sanda action based on 3D image reconstruction. First, the method relies on frame adjacent phase compensation and digital image stabilization techniques to perform digital frame operations on the image. Then, scanning and corner detection are used for image reconstruction, where adjacent phase compensation methods are used to match feature points and gray pixels. Image extraction is performed by extracting key feature points of the action 3D image, and a fast frame detection method is used to stabilize the image of the digital image, thereby improving the image quality of image reconstruction. The experimental results show that the method has good image output effect and has a high application value in Sanda guidance and optimization.


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