Image processing strategy for object recognition in artificial vision based on salient object detection
10.3969/j.issn.1005-202X.2025.07.007
- VernacularTitle:基于显著目标检测的人工视觉物体识别图像处理策略
- Author:
Yan ZHANG
1
;
Ying ZHAO
;
Feng CAO
;
Guangmiao JIANG
;
Yang HE
;
Sheng WANG
;
Nan WANG
Author Information
1. 齐鲁理工学院计算机与信息工程学院,山东 济南 250200
- Publication Type:Journal Article
- Keywords:
visual prosthesis;
simulated prosthetic vision;
salient object detection;
object recognition;
image processing strategy
- From:
Chinese Journal of Medical Physics
2025;42(7):883-891
- CountryChina
- Language:Chinese
-
Abstract:
Objective To propose a image processing strategy based on salient object detection algorithm for optimizing the presentation of prosthetic visual information at a limited resolution level,aiming to detect and enhance the salient objects in the scene and remove the background information.Methods A salient object detection model combining CNN and Transformer was used to extract salient objects.On this basis,methods such as object magnification,contour enhancement and contrast enhancement were utilized to optimize the image information.Psychophysical experiments were carried out at 5 resolution levels(16×16,24×24,32×32,48×48 and 64×64).Results In the simulated prosthetic vision,this image processing strategy had a remarkable effect on improving the object recognition ability of the subjects.Regardless of the resolutions of 16×16,24×24,32×32,48×48 and 64×64,the proposed strategy achieved the highest recognition accuracies,specifically 34%±6%,56%±9%,72%±9%,89%±4%and 96%±2%.Conclusion Using the salient object detection method and image processing strategy to extract and enhance salient objects can help prosthesis implant recipients effectively improve their object recognition ability.
