Digital implementation of Shunting Inhibitory Cellular Neural Network

Tarik Hammadou, Abdesselam Bouzerdoum, Amine Bermak

Research output: Contribution to journalArticle

1 Citation (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 languageEnglish
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4067
Publication statusPublished - 2000
Externally publishedYes

Fingerprint

Shunting Inhibitory Cellular Neural Networks
Cellular neural networks
Computer hardware description languages
Image enhancement
Edge detection
Image processing
Hardware
Real-time Image Processing
Processing
Edge Enhancement
Contrast Enhancement
Hardware Architecture
Image Enhancement
Edge Detection
Dynamic Range
Vision System
hardware description languages
image enhancement
augmentation
edge detection

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Digital implementation of Shunting Inhibitory Cellular Neural Network. / Hammadou, Tarik; Bouzerdoum, Abdesselam; Bermak, Amine.

In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 4067, 2000.

Research output: Contribution to journalArticle

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