Edge Detection Based on Hodgkin-Huxley Neuron Model Simulation

Autor: Olivier Lezoray, Boudjelal Meftah, Abdelkader Benyettou, Hayat Yedjour
Přispěvatelé: Laboratoire Signal Image et Parole (SIMPA), Université Mohamed Boudiaf de M'sila, Equipe Image - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Computer science
Cognitive Neuroscience
Models
Neurological
Experimental and Cognitive Psychology
02 engineering and technology
Edge detection
03 medical and health sciences
0302 clinical medicine
Artificial Intelligence
Orientation
0202 electrical engineering
electronic engineering
information engineering
medicine
Humans
Computer Simulation
Computer vision
Vision
Ocular
Visual Cortex
Network model
Neurons
Spiking neural network
Computational neuroscience
business.industry
Orientation (computer vision)
General Medicine
Hodgkin–Huxley model
Visual cortex
medicine.anatomical_structure
Receptive field
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
020201 artificial intelligence & image processing
Neural Networks
Computer
Artificial intelligence
business
030217 neurology & neurosurgery
Zdroj: Cognitive Processing
Cognitive Processing, Springer Verlag, 2017, 18 (3), pp.315-323. ⟨10.1007/s10339-017-0803-z⟩
ISSN: 1612-4782
1612-4790
DOI: 10.1007/s10339-017-0803-z⟩
Popis: International audience; In this paper, we propose a spiking neural network model for edge detection in images. The proposed model is biologically inspired by the mechanisms employed by natural vision systems, more specifically by the biologically fulfilled function of simple cells of the human primary visual cortex that are selective for orientation. Several aspects are studied in this model according to three characteristics: feedforward spiking neural structure; conductance-based model of the Hodgkin-Huxley neuron and Gabor receptive fields structure. A visualized map is generated using the firing rate of neurons representing the orientation map of the visual cortex area. We have simulated the proposed model on different images. Successful computer simulation results are obtained. For comparison, we have chosen five methods for edge detection. We finally evaluate and compare the performances of our model toward contour detection using a public dataset of natural images with associated contour ground truths. Experimental results show the ability and high performance of the proposed network model.
Databáze: OpenAIRE
Externí odkaz: