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: Contribution to journal › Conference article › peer-review

2 Citations (Scopus)

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
Pages (from-to)	904-912
Number of pages	9
Journal	Unknown Journal
Volume	4067 (II)
DOIs	https://doi.org/10.1117/12.386692
Publication status	Published - 2000
Externally published	Yes
Event	Visual Communications and Image Processing 2000 - Perth, Aust Duration: 20 Jun 2000 → 23 Jun 2000

Access to Document

10.1117/12.386692

Cite this

@article{c6396766f8094e278e19642cf940efa2,

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",

volume = "4067 (II)",

pages = "904--912",

journal = "Unknown Journal",

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

}

TY - JOUR

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 - http://www.scopus.com/inward/record.url?scp=0033715892&partnerID=8YFLogxK

U2 - 10.1117/12.386692

DO - 10.1117/12.386692

M3 - Conference article

AN - SCOPUS:0033715892

VL - 4067 (II)

SP - 904

EP - 912

JO - Unknown Journal

JF - Unknown Journal

T2 - Visual Communications and Image Processing 2000

Y2 - 20 June 2000 through 23 June 2000

ER -

Digital implementation of Shunting Inhibitory Cellular Neural Network

Abstract

Access to Document

Other files and links

Fingerprint

Cite this