TENSOR AND VECTOR APPROACHES TO OBJECTS RECOGNITION BY INVERSE FEATURE FILTERS


PODEJŚCIE TENSOROWE I WEKTOROWE DO ROZPOZNAWANIA OBIEKTÓW ZA POMOCĄ FILTRÓW CECH ODWROTNYCH
Kvyetnyy R. Bunyak Y. Sofina O. Kotsiubynskyi V. Piliavoz T. Stoliarenko O. Kumargazhanova S.
2024Politechnika Lubelska

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Srodowiska
2024#14Issue 141 - 45 pp.

The investigation of the extraction of image objects features by filters based on tensor and vector data presentation is considered. The tensor data is obtained as a sum of rank-one tensors, given by the tensor product of the vector of lexicographic representation of image fragments pixels with itself. The accumulated tensor is approximated by one rank tensor obtained using singular values decomposition. It has been shown that the main vector of the decomposition can be considered as the object feature vector. The vector data is obtained by accumulating analogous vectors of image fragments pixels. The accumulated vector is also considered as an object feature. The filter banks of a set of objects are obtained by regularized inversion of the matrices compiled by object features vectors. Optimized regularization of the inversion is used to expand the regions of object features capture with minimal error. The object fragments and corresponding feature vectors are selected through a training iterative process. The tensor and vector approaches create two channels for recognition. High efficiency of object recognition can be achieved by choosing the filter capture band and creating filter branches according to the given bands. The filters create a convolutional network to recognize a set of objects. It has been shown that the obtained filters have an advantage over known correlation filters when recognizing objects with small fragments.

image data tensor , image data vector , inverse filters , objects feature , objects recognition , optimized regularization

Text of the article Перейти на текст статьи

Vinnitsia National Technical University, Vinnitsia, Ukraine
Spilna Sprava company, Vinnitsia, Ukraine
Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University, Vinnitsia, Ukraine
D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk, Kazakhstan

Vinnitsia National Technical University
Spilna Sprava company
Vinnytsia Mykhailo Kotsiubynskyi State Pedagogical University
D. Serikbayev East Kazakhstan Technical University

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026