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Related Experiment Video

Updated: Jul 2, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Neuromorphic VLSI vision system for real-time texture segregation.

Kazuhiro Shimonomura1, Tetsuya Yagi

  • 1The Center for Advanced Medical Engineering and Informatics, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan.

Neural Networks : the Official Journal of the International Neural Network Society
|August 30, 2008
PubMed
Summary

This study developed novel hardware for real-time texture segregation, inspired by the brain's visual cortex. The system mimics neural processing for efficient visual perception.

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Visual System01:26

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...

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Area of Science:

  • Neuroscience
  • Computer Engineering
  • Artificial Intelligence

Background:

  • The brain's visual system achieves real-time scene perception with low power, despite slow individual neuron speeds.
  • The hierarchical and parallel architecture of visual cortex receptive fields is key for designing advanced perception systems.

Purpose of the Study:

  • To develop a novel vision system hardware inspired by hierarchical visual processing in V1 for real-time texture segregation.
  • To emulate neural circuits for efficient and accurate visual data processing.

Main Methods:

  • A multi-chip system comprising a silicon retina, an orientation chip, and a field-programmable gate array (FPGA) circuit was designed.
  • The system emulates vertebrate retinal neural circuits and uses Gabor-like receptive fields tuned to various orientations.

Related Experiment Videos

Last Updated: Jul 2, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

  • FPGA computed complex cell responses and enabled real-time texture segregation using orientation-selective outputs.

    • Main Results:

    • The developed hardware successfully computed neural images of simple cells in real-time for diverse orientations and spatial frequencies.
    • Real-time texture segregation was achieved by filtering images with orthogonally oriented receptive fields and processing with FPGA.
    • The system demonstrated effective segregation of texture areas based on orientation differences.

    Conclusions:

    • The developed bio-inspired hardware provides a platform for real-time texture segregation, mimicking biological visual processing.
    • This system offers a valuable tool for investigating higher-order cell functions within the visual pathway.
    • The research advances the engineering of perception systems by leveraging principles from neuroscience and psychophysics.