Use of Cellular Automata to Create an Artificial System of Image Classification and Recognition

Belan, Stepan; Belan, Nikolay

doi:10.1007/978-3-642-33350-7_50

Cited by 8 publications

(5 citation statements)

References 5 publications

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“…In his work, J. von Neumann says that the computing environment is a homogeneous field, which consists of an array of processor elements (PE). Each PE contains vertically and horizontally homogeneous connections with neighboring PEs [1,2,6]. Neighborhoods that connect each PE environment with two horizontal and two vertical neighbors and has connections with diagonally neighboring PE are called neighborhoods Moore [2].…”

Section: Main Characteristics Of Cellurlar Automatamentioning

confidence: 99%

“…It implements a signal transmission from one cell to another leading to a unit state. This was described in detail in [1,2]. The compression ratio of the binary image is determined by compression ratio …”

Section: Signal Is Identified Before the Interference Of Noise Signalsmentioning

confidence: 99%

“…They can be considered as a branch of science or the scope of industrial activity, where they are used or will be used in the coming years. These methods and tools are used in the field of automatic control of product quality, compression of data arrays in communication channels, identification of objects, video processing, pattern recognition and identification of objects, compression and processing of graphic information [1][2][3][4]. In this paper, we propose a method with hardware for optimal encoding of images by extracting the information elements using cellular automata methodology.…”

Section: Introductionmentioning

confidence: 99%

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Encoding Binary Images using Cellular Automata for Data Compression

Bdour¹

2014

IJCA

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Section: Main Characteristics Of Cellurlar Automatamentioning

confidence: 99%

Section: Signal Is Identified Before the Interference Of Noise Signalsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Encoding Binary Images using Cellular Automata for Data Compression

Bdour¹

2014

IJCA

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“…Particularly effective is the use of cellular automata (S. Belan & N. Belan, 2012;Bandini, Bonomi, & Vizzari, 2012;Ioannidis, Andreadis, & Sirakoulis, 2012). With their help it is easy to implement parallel processing of data arrays.…”

Section: Introductionmentioning

confidence: 99%

A Homogenous Parameter Set for Image Recognition Based on Area

Belan¹,

Yuzhakov²

2013

CIS

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This paper considers a method of image recognition, which is produced by the transformation of the object into a set of functions representing the area of intersection of the figure and its copy at its shift in one direction. The object of this research is image shapes of individual objects in the visual picture. The efficiency of different methods of optical image recognition has been conducted depending on the scale and rotation angle.

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“…There is a need to put in the basis of systems of vision simple methods of operation with video data (Belan & Yuzhakov, 2002Belan & Belan, 2012;Belan & Motornyuk, 2013). Such methods of image processing can be done using parallel shift technology (PST).…”

Section: Introductionmentioning

confidence: 99%

Machine Vision System Based on the Parallel Shift Technology and Multiple Image Analysis

Belan¹,

Yuzhakov²

2013

CIS

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This article describes basic methods that are required to build a system of machine vision which based on parallel shift technology. The methods are based on the implementation of one operation (definition function of the area of intersection of the real image and its copy which parallel shifted) and analysis of its basic characteristics. Analysis of time intervals obtained characteristics improves the performance of image recognition. The methods are based on simple mathematical operations and can be used in the processing of both raster and non-raster images.

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Use of Cellular Automata to Create an Artificial System of Image Classification and Recognition

Cited by 8 publications

References 5 publications

Encoding Binary Images using Cellular Automata for Data Compression

Encoding Binary Images using Cellular Automata for Data Compression

A Homogenous Parameter Set for Image Recognition Based on Area

Machine Vision System Based on the Parallel Shift Technology and Multiple Image Analysis

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