International automatic font size system and method

• US 20040119714A1
• Filed: 12/18/2002
• Published: 06/24/2004
• Est. Priority Date: 12/18/2002
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Byers, James D., Everett, Nathan W., McDonald, Marc B.
• Application Number:
  US10/323,038
• Publication Number:
  US 20040119714A1
• Time in Patent Office: Days
• US Class Current: 345/471
• CPC Class Codes: G06F 40/109 Font handling; Temporal or kinetic typography

Abstract

A system and method determines an optimum size for a font for readability. A method determines font characteristics by determining a character density for the font and multiplying the character density by a sharpest focusable area of the viewing medium. The method further includes varying the character density according to a range in a number of clusters per fixation to determine a maximum font size and a minimum font size. In an embodiment, the character density is a ratio of a number of clusters per em in the font to a number of visible clusters within a predetermined foveal angle. The predetermined foveal angle can be a field of vision for sharpest focus of an eye or a reader specific foveal angle that reflects the reader'"'"'s visual acuity, taking into consideration macular degeneration, vision impairments, vision sharpness, tunnel vision, eye disease, near sightedness, far sightedness, dyslexia, and astigmatism.

Claims

1. A method for automatically determining an optimum size for a font for readability on a viewing medium, the font capable of rendering text, the text organized in clusters, each cluster being a rendering unit of the string of text identified by an amount of printed matter between points where a cursor can be inserted therein, the text being rendered in a font size, the font size being in terms of an em, each em identified by a square of the type, the method comprising:

determining a character density for the font; and

multiplying the character density by a sharpest focusable area of the viewing medium.

2. A device for implementing the method of claim 1, the device accepting a width of the viewing medium and a distance from the viewing medium as inputs and providing as an output the optimum size and line height for the font using the determined character density and the multiplied sharpest focusable area.

3. The device of claim 2 wherein the output is available to the viewing medium over a network.

4. The device of claim 2 wherein the device is one of a handheld computing device, a computer, a portable computing device, and a microprocessing unit installed within a printer.

5. The method of claim 1 further comprising:

determining an appropriate font size for the viewing medium based on the multiplied character density and sharpest focusable area; and

enabling the viewing medium to render the optimum sized font.

6. The method of claim 5 wherein at least the determining is performed on a computer.

7. The method of claim 5 wherein the determining is performed on a computer and the viewing medium is one or more of a printed page, a screen, a wirelessly connected viewing medium, a billboard, an image and a font-rendering medium.

8. The method of claim 1 further comprising:

varying the character density according to a range in a number of clusters per fixation to determine a maximum font size and a minimum font size, the number of clusters per fixation being a function of language characteristics.

9. The method of claim 1 wherein the sharpest focusable area is determined using a trigonometric function of a foveal angle and a distance from the viewing medium.

10. The method of claim 1 wherein the character density is a function of graphic density and information density of a cluster.

11. The method of claim 10 wherein the graphic density and information density are language dependent, including reading characteristics of the language, the information density providing an amount of information per sharpest focused area viewable to a reader.

12. The method of claim 1 wherein the character density is a ratio of a number of clusters per em in the font to a number of visible clusters within a predetermined foveal angle.

13. The method of claim 1 wherein the sharpest focusable area is twice the tangent of half of a predetermined foveal angle multiplied by the distance from the viewing surface.

14. The method of claim 12 wherein the predetermined foveal angle is a field of vision for sharpest focus of an eye.

15. The method of claim 13 wherein half of the predetermined foveal angle in radians is about 0.006544;

and the predetermined foveal angle is about 0.75 degrees.

16. The method of claim 12 wherein the predetermined foveal angle is a variable determined by one or more of:

an input of a reader specific foveal angle; and

a foveal angle of approximately 0.75 degrees.

17. The method of claim 16 wherein the reader specific foveal angle reflects the reader'"'"'s visual acuity, the reader specific foveal angle taking into consideration one or more of macular degeneration, vision impairments, vision sharpness, tunnel vision, eye disease, near sightedness, far sightedness, dyslexia, and astigmatism.

18. A system for adjusting text in a font for optimal readability on a viewing medium, the system comprising:

a data structure configured to hold one or more text parameters; and

a reading metrics engine coupled to the data structure, the reading metrics engine configured to receive the one or more parameters of the text, the reading metrics engine including

a module configured to determine a character density for the font; and

a module configured to multiply the character density by a sharpest focusable area of an eye to produce an optimal size of the font for readability.

19. The system of claim 18 wherein the reading metrics engine further comprises:

a module configured to determine an optimum column width via a function of the optimal size of the font, a number of clusters per fixation for a language type, a number of clusters per em and a distance from the viewing medium.

20. The system of claim 19 wherein the number of clusters per fixation is determined according to a table, the table providing a plurality of clusters per fixation according to language.

21. The system of claim 19 wherein the number of clusters per fixation for the language type is a constant associated with one of a plurality of languages, each of the plurality of languages having a representative constant representing a graphic density and an information density for reading in the language.

22. The system of claim 18 further comprising:

a rendering device for the viewing medium, the viewing surface being one of a printed page, a computer screen, a personal digital assistant, a holographic image, a billboard, movie screen and an insert in a pair of glasses.

23. The system of claim 18 wherein the sharpest focusable area of the eye is determined by via a distance from a viewing medium and a foveal angle.

24. A system for automatically determining an optimum size for a font for readability on a viewing medium, the font capable of rendering text, the text organized in clusters, each cluster being a rendering unit of the string of text identified by an amount of printed matter between points where a cursor can be inserted therein, the text being rendered in a font size, the font size being in terms of an em, each em identified by a square of the type, the system comprising:

an application configured to display text;

a layout engine coupled to receive and transmit data to the application, the layout engine including;

a structure and layout input filter coupled to receive data from the application;

a text engine configured to determine a character density for the font; and

a reading metrics engine configured to multiply the character density by a sharpest focusable area of the viewing medium.

25. The system of claim 24 wherein the layout engine further includes an international translator coupled to provide data to one or more of the structure and layout input filter and the application for rendering the text on the viewing medium.

26. The system of claim 24 wherein the reading metrics engine includes:

a clusters per best readable line module configured to receive a clusters per fixation parameter from a language table;

a clusters per line module coupled to the clusters per best readable line module, the clusters per line configured to determine a minimum and maximum clusters per line parameter;

an column width module coupled to the clusters per line module, the column width module configured to determine a minimum and maximum column width; and

a column count module coupled to the column width module, the column count module configured to determine column count using mark up and system-provided window measurements.

27. The system of claim 24 wherein the reading metrics module includes:

a readable font size module coupled to receive the character density, the readable font size module using a clusters per em calculation and a clusters per fixation to determine the font size.

28. The system of claim 27 wherein the font size is based on a distance from the viewing medium.

29. The system of claim 26 wherein the column width is determined by dividing the font size by a product of clusters per em and clusters per line.

30. The system of claim 26 wherein the column width is determined by determining an actual live matter width according to display dimensions and user preference and dividing the actual live matter width by a function of a font size and cluster dimensions.

31. The system of claim 24 wherein the reading metrics module includes:

a heading line height module coupled to receive the character density, a clusters per line parameter and a live matter parameter to determine a heading font size.

32. A computer readable medium having computer-executable instructions for determining an optimum font size for readability on a viewing surface the instructions comprising the steps of:

determining a character density for a font; and

multiplying the character density by a length of a sharpest focus area of an eye.

33. The computer readable medium of claim 32, further comprising:

varying the character density according to a range in a number of clusters per fixation to determine a maximum font size and a minimum font size, the number of clusters per fixation being a function of language characteristics.

34. The computer readable medium of claim 32 wherein the sharpest focusable area is determined using a trigonometric function of a foveal angle and a distance from the viewing medium.

35. The computer readable medium of claim 32 wherein the character density is a function of graphic density and information density of a cluster.

36. The computer readable medium of claim 35 wherein the graphic density and information density are language dependent, including reading characteristics of the language, the information density providing an amount of information per sharpest focused area viewable to a reader.

38. The computer readable medium of claim 32 wherein the sharpest focusable area is twice the tangent of half of a predetermined foveal angle multiplied by the distance from the viewing surface.

39. The computer readable medium of claim 38 wherein the predetermined foveal angle is related to a field of vision for sharpest focus of an eye.

40. The computer readable medium of claim 38 wherein half of the predetermined foveal angle in radians is about 0.006544;

and the predetermined foveal angle is about 0.75 degrees.

41. The computer readable medium of claim 38 wherein the predetermined foveal angle is a variable determined by one or more of:

an input of a reader specific foveal angle; and

a foveal angle of approximately 0.75 degrees.

42. The computer readable medium of claim 41 wherein the reader specific foveal angle reflects the reader'"'"'s visual acuity, the reader specific foveal angle taking into consideration one or more of macular degeneration, vision impairments, vision sharpness, tunnel vision, eye disease, near sightedness, far sightedness, dyslexia, and astigmatism.

37. The computer readable medium of 32 wherein the character density is a ratio of a number of clusters per em in the font to a number of visible clusters within a predetermined foveal angle.