Literature DB >> 24117959

Recognition of objects in simulated irregular phosphene maps for an epiretinal prosthesis.

Yanyu Lu1, Jing Wang, Hao Wu, Liming Li, Xun Cao, Xinyu Chai.   

Abstract

Visual prostheses offer a possibility of restoring vision to the blind. It is necessary to determine minimum requirements for daily visual tasks. To investigate the recognition of common objects in daily life based on the simulated irregular phosphene maps, the effect of four parameters (resolution, distortion, dropout percentage, and gray scale) on object recognition was investigated. The results showed that object recognition accuracy significantly increased with an increase of resolution. Distortion and dropout percentage had significant impact on the object recognition; with the increase of distortion level and dropout percentage, the recognition decreased considerably. The accuracy decreased significantly only at gray level 2, whereas the other three gray levels showed no obvious difference. The two image processing methods (merging pixels to lower the resolution and edge extraction before lowering resolution) showed significant difference on the object recognition when there was a high degree of distortion level or dot dropout.
© 2013 Wiley Periodicals, Inc. and International Center for Artificial Organs and Transplantation.

Keywords:  Irregular phosphene map; Object recognition; Pixelized image; Simulated prosthetic vision; Visual prosthesis

Mesh:

Year:  2013        PMID: 24117959     DOI: 10.1111/aor.12174

Source DB:  PubMed          Journal:  Artif Organs        ISSN: 0160-564X            Impact factor:   3.094


  2 in total

1.  Optimization of Visual Information Presentation for Visual Prosthesis.

Authors:  Fei Guo; Yuan Yang; Yong Gao
Journal:  Int J Biomed Imaging       Date:  2018-03-14

2.  Semantic and structural image segmentation for prosthetic vision.

Authors:  Melani Sanchez-Garcia; Ruben Martinez-Cantin; Jose J Guerrero
Journal:  PLoS One       Date:  2020-01-29       Impact factor: 3.240

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.