Classification of Images Based on a System of Hierarchical Features

被引:5
作者
Daradkeh, Yousef Ibrahim [1 ]
Gorokhovatskyi, Volodymyr [2 ]
Tvoroshenko, Iryna [2 ]
Al-Dhaifallah, Mujahed [3 ,4 ]
机构
[1] Prince Sattam Bin Abdulaziz Univ, Coll Engn Wadi Addawasir, Dept Comp Engn & Networks, Al Kharj 11991, Saudi Arabia
[2] Kharkiv Natl Univ Radio Elect, Dept Informat, UA-61166 Kharkiv, Ukraine
[3] King Fand Univ Petr & Minerals, Control & Instrumentat Engn Dept, Dhahran 31261, Saudi Arabia
[4] King Fand Univ Petr & Minerals, Interdisciplinary Res Ctr IRC Renewable Energy &, Dhahran 31261, Saudi Arabia
来源
CMC-COMPUTERS MATERIALS & CONTINUA | 2022年 / 72卷 / 01期
关键词
Bitwise distribution; computer vision; descriptor; hierarchical rep-; resentation; image classification; keypoint; noise immunity; processing speed; ALGORITHM; MODEL;
D O I
10.32604/cmc.2022.025499
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1785 / 1797
页数:13
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