Open AccessAnalysis of the features of image processing using the Hamming network on the STM-32 microcontroller
Author(s) -
A O Chepkov,
V.S. Klimachev,
А.Ю. Корчагин,
Andrey I. Vlasov
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1889/2/022046
Subject(s) - microcontroller , computer science , artificial neural network , hamming distance , hamming code , artificial intelligence , process (computing) , image processing , pattern recognition (psychology) , class (philosophy) , image (mathematics) , noise (video) , similarity (geometry) , computer vision , algorithm , computer hardware , decoding methods , operating system , block code
The paper discusses the features of solving a class of problems for pattern recognition using the STM-32 microcontroller. The problem of pattern recognition can be solved on neural networks of different architectures, the main attention is paid to the Hamming neural network model. The features of the implementation of the Hamming network based on the STM-32 microcontroller for the recognition of images entered via the touch screen are analyzed. It is experimentally shown that the network cannot always correctly process the input value and compare it with the reference value of the class for digital test images. This is due to the high degree of similarity of some images and the presence of noise. In conclusion, recommendations on the implementation of neural network algorithms for image processing on microcontrollers are given.