Method for optimizing optical aids by automatically determining subjective visual acuity

A technology for automatic determination and visual acuity, applied in the direction of optical components, non-optical accessories, neural learning methods, etc., can solve problems such as laborious optical aids, inaccurate destructive effects, and inability to guarantee sufficiently accurate results
CN112584750BActive Publication Date: 2022-07-08CARL ZEISS VISION INT GMBH
6 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CARL ZEISS VISION INT GMBH
Publication Date
2022-07-08

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention relates to: a method for optimizing optical aids by automatically measuring subjective visual acuity; a method for producing correspondingly optimized optical aids; a device for producing optical aids; a A computer program having program code for executing the optimization method, the program being executable on a processor; and a non-transitory storage medium including the computer program stored thereon.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The present invention relates to a method for optimizing optical aids by automatically determining subjective visual acuity. Background technique

[0002] Known methods for determining subjective visual acuity (eg, the resolution of the human eye) are based on the assumption that there is a link between optical defects and expected visual acuity. These known methods model the visual system through various optical and neural filter functions. This modeling is based on subjective measurements of test subjects. Subjective subjective measurements are laborious and result in skewed results due to disruptive effects (eg, due to test subject fatigue). Furthermore, the filter function has adjustable weights that must be adapted appropriately. In particular, neural transfer functions can be highly nonlinear and thus difficult to describe. The neural transfer function can vary greatly from person to person. Therefore, using these known methods cannot guaran...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More