Content-Based 3D Retrieval by Krawtchouk Moments

2006 ◽  
pp. 217-224 ◽  
Author(s):  
Pan Xiang ◽  
Chen Qihua ◽  
Liu Zhi
Keyword(s):  
Krawtchouk Moments ◽  
3D Retrieval

Real-time Computation of Krawtchouk Moments on Gray Images Using Block Representation

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Nikolaos D. Karampasis ◽  
Iraklis M. Spiliotis ◽  
Yiannis S. Boutalis
Keyword(s):  
Real Time ◽  
Krawtchouk Moments

scholarly journals The Development and Applications of Ultrafast Electron Nanocrystallography

2009 ◽  
Vol 15 (4) ◽  
pp. 323-337 ◽  
Author(s):  
Chong-Yu Ruan ◽  
Yoshie Murooka ◽  
Ramani K. Raman ◽  
Ryan A. Murdick ◽  
Richard J. Worhatch ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Structural Dynamics ◽  
Atomic Scale ◽  
Energy Redistribution ◽  
Gold Nanocrystals ◽  
Charge Dynamics ◽  
Atomic Structures ◽  
Molecular Scale ◽  
Spatio Temporal ◽  
3D Retrieval

AbstractWe review the development of ultrafast electron nanocrystallography as a method for investigating structural dynamics for nanoscale materials and interfaces. Its sensitivity and resolution are demonstrated in the studies of surface melting of gold nanocrystals, nonequilibrium transformation of graphite into reversible diamond-like intermediates, and molecular scale charge dynamics, showing a versatility for not only determining the structures, but also the charge and energy redistribution at interfaces. A quantitative scheme for 3D retrieval of atomic structures is demonstrated with few-particle (<1,000) sensitivity, establishing this nanocrystallographic method as a tool for directly visualizing dynamics within isolated nanomaterials with atomic scale spatio-temporal resolution.

New Set of Invariant Quaternion Krawtchouk Moments for Color Image Representation and Recognition

2021 ◽  
pp. 2250037
Author(s):  
Gaber Hassan ◽  
Khalid M. Hosny ◽  
R. M. Farouk ◽  
Ahmed M. Alzohairy
Keyword(s):  
Quaternion Algebra ◽  
Color Image ◽  
Image Representation ◽  
Color Images ◽  
Color Channel ◽  
Krawtchouk Polynomials ◽  
Krawtchouk Moments ◽  
Similarity Transformations ◽  
The Stability ◽  
Discrete Moments

One of the most often used techniques to represent color images is quaternion algebra. This study introduces the quaternion Krawtchouk moments, QKrMs, as a new set of moments to represent color images. Krawtchouk moments (KrMs) represent one type of discrete moments. QKrMs use traditional Krawtchouk moments of each color channel to describe color images. This new set of moments is defined by using orthogonal polynomials called the Krawtchouk polynomials. The stability against the translation, rotation, and scaling transformations for QKrMs is discussed. The performance of the proposed QKrMs is evaluated against other discrete quaternion moments for image reconstruction capability, toughness against various types of noise, invariance to similarity transformations, color face image recognition, and CPU elapsed times.

A New Object Recognition Approach Using Combination of Texture, Color and Shape Features

2015 ◽  
Vol 761 ◽  
pp. 111-115
Author(s):  
Abdul Kadir ◽  
K.A.A. Aziz ◽  
Irianto
Keyword(s):  
Texture Features ◽  
Shape Features ◽  
Accuracy Rate ◽  
New Approach ◽  
Orthogonal Moments ◽  
Krawtchouk Moments ◽  
Image Histogram ◽  
Color Features ◽  
Tchebichef Moments ◽  
Skewness And Kurtosis

This paper reports a new approach for recognizing objects by using combination of texture, color and shape features. Texture features were generated by applying statistical calculation on the image histogram. Color features were computed by using mean, standard deviation, skewness and kurtosis. Shape features were generated using combination of Shen features and basic shapes such as eccentricity and dispersion. The total features were used much less compared to approaches that involve orthogonal moments such as Krawtchouk moments, Zernike moments, or Tchebichef moments. Testing was done by using a dataset that contains 53 kinds of objects. All objects contained in the dataset were various things that can be found in supermarkets or produced by manufacturing. The result shows that the system gave 98.11% of accuracy rate.

Image reconstruction by Krawtchouk moments via digital filter

2017 ◽  
Author(s):  
Hicham Karmouni ◽  
Tarik Jahid ◽  
Zouhir Lakhili ◽  
Abdeslam Hmimid ◽  
Mhamed Sayyouri ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Digital Filter ◽  
Krawtchouk Moments
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