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Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model
The Hubel–Wiesel (HW) model is a classical neurobiological model for explaining the orientation selectivity of cortical cells. However, the HW model still has not been fully proved physiologically, and there are few concise but efficient systems to quantify and simulate the HW model and can be used...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9025109/ https://www.ncbi.nlm.nih.gov/pubmed/35448001 http://dx.doi.org/10.3390/brainsci12040470 |
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author | Li, Bin Todo, Yuki Tang, Zheng |
author_facet | Li, Bin Todo, Yuki Tang, Zheng |
author_sort | Li, Bin |
collection | PubMed |
description | The Hubel–Wiesel (HW) model is a classical neurobiological model for explaining the orientation selectivity of cortical cells. However, the HW model still has not been fully proved physiologically, and there are few concise but efficient systems to quantify and simulate the HW model and can be used for object orientation detection applications. To realize a straightforward and efficient quantitive method and validate the HW model’s reasonability and practicality, we use McCulloch-Pitts (MP) neuron model to simulate simple cells and complex cells and implement an artificial visual system (AVS) for two-dimensional object orientation detection. First, we realize four types of simple cells that are only responsible for detecting a specific orientation angle locally. Complex cells are realized with the sum function. Every local orientation information of an object is collected by simple cells and subsequently converged to the corresponding same type complex cells for computing global activation degree. Finally, the global orientation is obtained according to the activation degree of each type of complex cell. Based on this scheme, an AVS for global orientation detection is constructed. We conducted computer simulations to prove the feasibility and effectiveness of our scheme and the AVS. Computer simulations show that the mechanism-based AVS can make accurate orientation discrimination and shows striking biological similarities with the natural visual system, which indirectly proves the rationality of the Hubel–Wiesel model. Furthermore, compared with traditional CNN, we find that our AVS beats CNN on orientation detection tasks in identification accuracy, noise resistance, computation and learning cost, hardware implementation, and reasonability. |
format | Online Article Text |
id | pubmed-9025109 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90251092022-04-23 Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model Li, Bin Todo, Yuki Tang, Zheng Brain Sci Article The Hubel–Wiesel (HW) model is a classical neurobiological model for explaining the orientation selectivity of cortical cells. However, the HW model still has not been fully proved physiologically, and there are few concise but efficient systems to quantify and simulate the HW model and can be used for object orientation detection applications. To realize a straightforward and efficient quantitive method and validate the HW model’s reasonability and practicality, we use McCulloch-Pitts (MP) neuron model to simulate simple cells and complex cells and implement an artificial visual system (AVS) for two-dimensional object orientation detection. First, we realize four types of simple cells that are only responsible for detecting a specific orientation angle locally. Complex cells are realized with the sum function. Every local orientation information of an object is collected by simple cells and subsequently converged to the corresponding same type complex cells for computing global activation degree. Finally, the global orientation is obtained according to the activation degree of each type of complex cell. Based on this scheme, an AVS for global orientation detection is constructed. We conducted computer simulations to prove the feasibility and effectiveness of our scheme and the AVS. Computer simulations show that the mechanism-based AVS can make accurate orientation discrimination and shows striking biological similarities with the natural visual system, which indirectly proves the rationality of the Hubel–Wiesel model. Furthermore, compared with traditional CNN, we find that our AVS beats CNN on orientation detection tasks in identification accuracy, noise resistance, computation and learning cost, hardware implementation, and reasonability. MDPI 2022-04-01 /pmc/articles/PMC9025109/ /pubmed/35448001 http://dx.doi.org/10.3390/brainsci12040470 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Bin Todo, Yuki Tang, Zheng Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model |
title | Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model |
title_full | Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model |
title_fullStr | Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model |
title_full_unstemmed | Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model |
title_short | Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model |
title_sort | artificial visual system for orientation detection based on hubel–wiesel model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9025109/ https://www.ncbi.nlm.nih.gov/pubmed/35448001 http://dx.doi.org/10.3390/brainsci12040470 |
work_keys_str_mv | AT libin artificialvisualsystemfororientationdetectionbasedonhubelwieselmodel AT todoyuki artificialvisualsystemfororientationdetectionbasedonhubelwieselmodel AT tangzheng artificialvisualsystemfororientationdetectionbasedonhubelwieselmodel |