TY - JOUR
T1 - Classification of Images Based on a System of Hierarchical Features
AU - Daradkeh, Yousef Ibrahim
AU - Gorokhovatskyi, Volodymyr
AU - Tvoroshenko, Iryna
AU - Al-Dhaifallah, Mujahed
N1 - Publisher Copyright:
© 2022 Tech Science Press. All rights reserved.
PY - 2022
Y1 - 2022
N2 - The results of the development of the new fast-speed method of classification images using a structural approach are presented. The method is based on the system of hierarchical features, based on the bitwise data distribution for the set of descriptors of image description. The article also proposes the use of the spatial data processing apparatus, which simplifies and accelerates the classification process. Experiments have shown that the time of calculation of the relevance for two descriptions according to their distributions is about 1000 times less than for the traditional voting procedure, for which the sets of descriptors are compared. The introduction of the system of hierarchical features allows to further reduce the calculation time by 2-3 times while ensuring high efficiency of classification. The noise immunity of the method to additive noise has been experimentally studied. According to the results of the research, the marginal degree of the hierarchy of features for reliable classification with the standard deviation of noise less than 30 is the 8-bit distribution. Computing costs increase proportionally with decreasing bit distribution. The method can be used for application tasks where object identification time is critical.
AB - The results of the development of the new fast-speed method of classification images using a structural approach are presented. The method is based on the system of hierarchical features, based on the bitwise data distribution for the set of descriptors of image description. The article also proposes the use of the spatial data processing apparatus, which simplifies and accelerates the classification process. Experiments have shown that the time of calculation of the relevance for two descriptions according to their distributions is about 1000 times less than for the traditional voting procedure, for which the sets of descriptors are compared. The introduction of the system of hierarchical features allows to further reduce the calculation time by 2-3 times while ensuring high efficiency of classification. The noise immunity of the method to additive noise has been experimentally studied. According to the results of the research, the marginal degree of the hierarchy of features for reliable classification with the standard deviation of noise less than 30 is the 8-bit distribution. Computing costs increase proportionally with decreasing bit distribution. The method can be used for application tasks where object identification time is critical.
KW - Bitwise distribution
KW - Computer vision
KW - Descriptor
KW - Hierarchical representation
KW - Image classification
KW - Keypoint
KW - Noise immunity
KW - Processing speed
UR - http://www.scopus.com/inward/record.url?scp=85125410473&partnerID=8YFLogxK
U2 - 10.32604/cmc.2022.025499
DO - 10.32604/cmc.2022.025499
M3 - Article
AN - SCOPUS:85125410473
SN - 1546-2218
VL - 72
SP - 1785
EP - 1797
JO - Computers, Materials and Continua
JF - Computers, Materials and Continua
IS - 1
ER -