Digital implementation of Shunting Inhibitory Cellular Neural Network

Tarik Hammadou; Abdesselam Bouzerdoum; Amine Bermak

doi:10.1117/12.386692

Digital implementation of Shunting Inhibitory Cellular Neural Network

Tarik Hammadou^*
, Abdesselam Bouzerdoum
, Amine Bermak

^*Corresponding author for this work

Edith Cowan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Shunting inhibition is a model of early visual processing which can provide contrast and edge enhancement, and dynamic range compression. An architecture of digital Shunting Inhibitory Cellular Neural Network (SICNN) for real time image processing is presented. The proposed architecture is intended to be used in a complete vision system for edge detection and image enhancement. The present hardware architecture, is modeled and simulated in VHDL. Simulation results show the functional validity of the proposed architecture.

Original language	English
Title of host publication	Visual Communications and Image Processing 2000
Publisher	Society of Photo-Optical Instrumentation Engineers
Pages	904-912
Number of pages	9
Volume	4067 4067
ISBN (Print)	0819437034
DOIs	https://doi.org/10.1117/12.386692
Publication status	Published - 2000
Externally published	Yes
Event	2000 Visual Communications and Image Processing, VCIP 2000 - Perth, Aust, Australia Duration: 20 Jun 2000 → 23 Jun 2000

Conference

Conference	2000 Visual Communications and Image Processing, VCIP 2000
Country/Territory	Australia
City	Perth, Aust
Period	20/06/00 → 23/06/00

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10.1117/12.386692

Cite this

@inproceedings{941f53d232cd4fdb8241c528ccac1aee,

title = "Digital implementation of Shunting Inhibitory Cellular Neural Network",

abstract = "Shunting inhibition is a model of early visual processing which can provide contrast and edge enhancement, and dynamic range compression. An architecture of digital Shunting Inhibitory Cellular Neural Network (SICNN) for real time image processing is presented. The proposed architecture is intended to be used in a complete vision system for edge detection and image enhancement. The present hardware architecture, is modeled and simulated in VHDL. Simulation results show the functional validity of the proposed architecture.",

author = "Tarik Hammadou and Abdesselam Bouzerdoum and Amine Bermak",

year = "2000",

doi = "10.1117/12.386692",

language = "English",

isbn = "0819437034",

volume = "4067 4067",

pages = "904--912",

booktitle = "Visual Communications and Image Processing 2000",

publisher = "Society of Photo-Optical Instrumentation Engineers",

note = "2000 Visual Communications and Image Processing, VCIP 2000 ; Conference date: 20-06-2000 Through 23-06-2000",

}

Hammadou, T, Bouzerdoum, A & Bermak, A 2000, Digital implementation of Shunting Inhibitory Cellular Neural Network. in Visual Communications and Image Processing 2000. vol. 4067 4067, Society of Photo-Optical Instrumentation Engineers, pp. 904-912, 2000 Visual Communications and Image Processing, VCIP 2000, Perth, Aust, Australia, 20/06/00. https://doi.org/10.1117/12.386692

TY - GEN

T1 - Digital implementation of Shunting Inhibitory Cellular Neural Network

AU - Hammadou, Tarik

AU - Bouzerdoum, Abdesselam

AU - Bermak, Amine

PY - 2000

Y1 - 2000

N2 - Shunting inhibition is a model of early visual processing which can provide contrast and edge enhancement, and dynamic range compression. An architecture of digital Shunting Inhibitory Cellular Neural Network (SICNN) for real time image processing is presented. The proposed architecture is intended to be used in a complete vision system for edge detection and image enhancement. The present hardware architecture, is modeled and simulated in VHDL. Simulation results show the functional validity of the proposed architecture.

AB - Shunting inhibition is a model of early visual processing which can provide contrast and edge enhancement, and dynamic range compression. An architecture of digital Shunting Inhibitory Cellular Neural Network (SICNN) for real time image processing is presented. The proposed architecture is intended to be used in a complete vision system for edge detection and image enhancement. The present hardware architecture, is modeled and simulated in VHDL. Simulation results show the functional validity of the proposed architecture.

UR - https://www.scopus.com/pages/publications/0033715892

U2 - 10.1117/12.386692

DO - 10.1117/12.386692

M3 - Conference contribution

AN - SCOPUS:0033715892

SN - 0819437034

VL - 4067 4067

SP - 904

EP - 912

BT - Visual Communications and Image Processing 2000

PB - Society of Photo-Optical Instrumentation Engineers

T2 - 2000 Visual Communications and Image Processing, VCIP 2000

Y2 - 20 June 2000 through 23 June 2000

ER -

Digital implementation of Shunting Inhibitory Cellular Neural Network

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