Modeling of a method of parallel hierarchical transformation for fast recognition of dynamic images

Timchenko, Leonid I.; Kokryatskaya, N.I.; Shpakovych, Viktoriya V.

doi:10.1186/1687-6180-2013-87

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…The results show a negligible rate distortion drop with a time reduction of up to 98% for the complete H.264/AVC encoder. The last article regarding this first topic is entitled 'Modeling of a method of parallel hierarchical transformation for fast recognition of dynamic images' [13] by Leonid Timchenko et al; the authors present principles necessary to develop a method, and computational facilities for the parallel hierarchical transformation based on highperformance GPUs are discussed in the paper. Mathematical models of the parallel hierarchical (PH) network training for the transformation and a PH network training method for recognition of dynamic images are developed.…”

Section: Specific Contributionsmentioning

confidence: 99%

Hardware implementation of machine vision systems: image and video processing

Botella

Garcı́a

Meyer-Bäse

2013

EURASIP J. Adv. Signal Process.

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This contribution focuses on different topics covered by the special issue titled 'Hardware Implementation of Machine vision Systems' including FPGAs, GPUS, embedded systems, multicore implementations for image analysis such as edge detection, segmentation, pattern recognition and object recognition/interpretation, image enhancement/restoration, image/video compression, image similarity and retrieval, satellite image processing, medical image processing, motion estimation, neuromorphic and bioinspired vision systems, video processing, image formation and physics based vision, 3D processing/coding, scene understanding, and multimedia.

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Section: Specific Contributionsmentioning

confidence: 99%

Hardware implementation of machine vision systems: image and video processing

Botella

Garcı́a

Meyer-Bäse

2013

EURASIP J. Adv. Signal Process.

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“…The transformation of set into set , which is defined by model (7), will be called the transformation operator -a type of -transformation that is:…”

mentioning

confidence: 99%

Analysis of the main provisions of the theory of parallel-hierarchical transformations

Tymchenko,

Stetsenko,

Kokryatskay

et al. 2023

Opt-el. Inf-Power Techn.

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The article presents an analysis of the main principles of parallel-hierarchical transformations theory. The continuous movement of society towards the automation of everyday life requires the creation of fundamentally new software and hardware solutions. Considering the current physical limitations of integrated circuits, it is evident that improving software processing is the way to go. The main problem lies in the increasing complexity of architecture and supporting such code. The ideas of parallel-hierarchical networks allow for a significant increase in processing speed through process parallelization while maintaining the relative simplicity of the software solution's architecture. The proposed structure of the parallel-hierarchical network allows for modelling the operation principle of a distributed neural network and forms a deterministic network using spatial-temporal division. The general rules of direct and inverse parallel-hierarchical transformation and their application to image recognition tasks are discussed. A block diagram of the algorithm for the basic model of nonlinear direct network transformation is shown. A mathematical model of direct parallel-hierarchical transformation is presented using an example. Compared to known numerical transformation methods involving simple operations like addition, the model enables complex functional signal processing in real-time scale, as well as unambiguity and reversibility with good convergence of the computational process.

show abstract

Modeling of a method of parallel hierarchical transformation for fast recognition of dynamic images

Cited by 2 publications

References 18 publications

Hardware implementation of machine vision systems: image and video processing

Hardware implementation of machine vision systems: image and video processing

Analysis of the main provisions of the theory of parallel-hierarchical transformations

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