Transportation vehicle, physiological state detection device, and physiological state detection method applied to transportation vehicle
US-2024374188-A1 · Nov 14, 2024 · US
US9854970B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9854970-B2 |
| Application number | US-201313773310-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 21, 2013 |
| Priority date | Feb 21, 2012 |
| Publication date | Jan 2, 2018 |
| Grant date | Jan 2, 2018 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
The present application includes methods, systems and computer readable storage devices for determining a color score for at least a portion of a biological tissue. The subject matter of the application is embodied in a method that includes obtaining a digital image of the biological tissue, and receiving a selection of a portion of the image as an evaluation area. The method also includes determining for each of a plurality of pixels within the evaluation area, a plurality of color components that are based on a Cartesian color space, and determining, from the color components, a hue value in a polar coordinate based color space. The method further includes determining a color value based on the hue value for each of the plurality of pixels, and assigning a color score to the evaluation area based on an average of the color values of the plurality of pixels.
Opening claim text (preview).
What is claimed is: 1. A computer implemented method for evaluating a condition of an ocular surface based on a color of the ocular surface, the method comprising: obtaining a digital image of at least a portion of the ocular surface; receiving a selection of a portion of the image as an evaluation area; for each of a plurality of pixels within the evaluation area: determining a plurality of color components that are based on a Cartesian color space, determining, from the color components, a hue value in a polar coordinate based hue-saturation-value (HSV) color space, selecting an angle range in accordance with a color associated with the ocular condition being evaluated, determining that the hue value lies within the angle range that represents the color associated with the condition being evaluated in a hue circle representation of the HSV color space, mapping the hue value to a scalar value within a predetermined range, in response to determining that the hue value lies within the angle range, selecting a function of one or both of the saturation and value components of the HSV color space, wherein the function is selected based on the condition being evaluated, and determining a color value as a product of the scalar value and the function of one or both of the saturation and value components of the HSV color space; and generating a color score for the evaluation area based on an average of the color values of the plurality of pixels, wherein the color score of the ocular surface relates to a quantitative evaluation of the condition of the ocular surface. 2. The method of claim 1 , wherein the digital image further comprises an area of reference white color. 3. The method of claim 2 , further comprising receiving a selection of at least a portion of the reference white color; determining an average gain associated with the portion of the reference white color; and applying the average gain to each of the plurality of pixels within the evaluation area. 4. The method of claim 1 wherein a parabolic curve is used in mapping the hue value to the scalar value within the predetermined range. 5. The method of claim 1 , wherein the selection of the evaluation area is received through a graphical user interface in which the digital image is presented. 6. The method of claim 5 , wherein the selection of the evaluation area is received as a polygonal area of the digital image selected through the graphical user interface. 7. The method of claim 1 , wherein the ocular surface comprises conjunctiva. 8. The method of claim 1 , wherein the Cartesian color space is an RGB color space. 9. The method of claim 1 , further comprising storing the color score and an association of the color score with the digital image. 10. The method of claim 1 , wherein the digital images are related to one or more of corneal neovascularization, fluorescein stained epithelial punctate keratitis and epithelial defects, eyelid and skin telangiectasia, and conjunctival/scleral pigmented lesions. 11. The method of claim 1 , wherein the angle range is determined based on whether the condition is a conjunctival condition or a corneal neovascularization condition. 12. The method of claim 3 , further comprising omitting an area of specular reflection from the portion of the reference white color in determining the average gain. 13. The method of claim 1 , wherein to evaluate conjunctival redness, the color value is determined as a product of the scalar value and a saturation component of the polar coordinate based color space. 14. The method of claim 1 , wherein to evaluate conjunctival/scleral pigmented lesions or fluorescein stained punctuate keratitis, the color value is determined as a product of the scalar value, a saturation component, and a brightness component of the polar coordinate based color space. 15. The method of claim 1 , further comprising scaling the color score within a predetermined range. 16. The method of claim 15 , wherein the predetermined range is 0-100.
Related publications grouped by family.
Answers are generated from the same data shown on this page.