Recognition of Similar Objects Using Simulated Prosthetic Vision
Recognition of Similar Objects Using Simulated Prosthetic Vision
复制标题
使用模拟假肢视觉识别相似物体
DOI：
10.1111/aor.12147
复制
发表时间：
2014-02-01
影响因子：
2.4
通讯作者：
Peng, Yinghong
中科院分区：
文献类型：
--
作者：
Hu, Jie;Xia, Peng;Peng, Yinghong
由于现有技术的局限性，即使是最先进的视觉假体，使用数百个电极将信号传递到视觉通路，也限制了感觉功能和视觉信息。为了识别瓶颈并指导假体设计，对正常视力的人进行视觉假体的心理物理学模拟是可取的。在这项研究中，我们使用心理物理实验来辨别具有相似轮廓的物体，以检验荧光体阵列参数(空间分辨率、灰度级、失真和脱落率)对模拟假眼视觉信息的影响。结果表明，在最佳条件下(分辨率：32×32，灰度级：8，畸变率：K=0，丢失率：0%)，提高了图像的空间分辨率和灰度数，降低了荧光灯的畸变率和丢失率，提高了识别性能，准确率达到78.5%。在组合参数测试中，对于k=0.1失真和10%丢弃的所有图像，都获得了显著的人脸识别准确率。与其他实验相比，我们发现不同的对象对参数的变化并不表现出特定的敏感度，即使在最佳条件下，视觉信息也远远不够。结果表明，视觉假体设备需要更高的空间分辨率和更多的灰度级，进一步研究图像处理策略以改善假体视觉是必要的，特别是当佩戴者需要完成更多简单的视觉任务时。
Due to the limitations of existing techniques, even the most advanced visual prostheses, using several hundred electrodes to transmit signals to the visual pathway, restrict sensory function and visual information. To identify the bottlenecks and guide prosthesis designing, psychophysics simulations of a visual prosthesis in normally sighted individuals are desirable. In this study, psychophysical experiments of discriminating objects with similar profiles were used to test the effects of phosphene array parameters (spatial resolution, gray scale, distortion, and dropout rate) on visual information using simulated prosthetic vision. The results showed that the increase in spatial resolution and number of gray levels and the decrease in phosphene distortion and dropout rate improved recognition performance, and the accuracy is 78.5% under the optimum condition (resolution: 32x32, gray level: 8, distortion: k=0, dropout: 0%). In combined parameter tests, significant facial recognition accuracy was achieved for all the images with k=0.1 distortion and 10% dropout. Compared with other experiments, we find that different objects do not show specific sensitivity to the changes of parameters and visual information is not nearly enough even under the optimum condition. The results suggests that higher spatial resolution and more gray levels are required for visual prosthetic devices and further research on image processing strategies to improve prosthetic vision is necessary, especially when the wearers have to accomplish more than simple visual tasks.