Image processing strategies based on saliency segmentation for object recognition under simulated prosthetic vision.

Journal: Artificial intelligence in medicine
Published Date: Jan 1, 2018

Abstract

BACKGROUND AND OBJECTIVE: Current retinal prostheses can only generate low-resolution visual percepts constituted of limited phosphenes which are elicited by an electrode array and with uncontrollable color and restricted grayscale. Under this visual perception, prosthetic recipients can just complete some simple visual tasks, but more complex tasks like face identification/object recognition are extremely difficult. Therefore, it is necessary to investigate and apply image processing strategies for optimizing the visual perception of the recipients. This study focuses on recognition of the object of interest employing simulated prosthetic vision.

Authors

  • Heng Li
    Department of Anesthesiology, Affiliated Nanhua Hospital, University of South China, Hengyang 421002, Hunan Province, China.
  • Xiaofan Su
    School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Jing Wang
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Han Kan
    School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Tingting Han
    School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Yajie Zeng
    School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Xinyu Chai
    School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. Electronic address: xychai@sjtu.edu.cn.

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