1. An image processing apparatus that converts image data expressed by sets of various tone values which express a color image into dot volume data related to dot formation density of various type dots which express different tone values per respective single dots, said image processing apparatus comprising:
a color conversion module that receives first image data expressed by sets of various tone values of a first color coordinate system and converts the first image data into second image data expressed by sets of the tone values of each color which comprises a second color coordinate system; and
a dot volume data conversion module that converts said second image data into dot volume data of said various type dots with respect to each color of said second color coordinate system,
wherein said color conversion module converts said first image data into second image data which are increased proportionally with the tone value relationship between said second image data kept in the same sequence, when said second image data is at least in a preset tone range where the smallest dots, which express the smallest tone value per respective single dots among the various type dots, are genarated, and
said dot volume data conversion module converts said second image data of which said tone value is increased proportionally into said dot volume data which have been corrected to be disembarrassed from said proportional increase.
2. An image processing apparatus in accordance with claim 1, wherein the image processing apparatus further comprises a proportionally increased color conversion table that records sets of various tone values of said first color coordinate system and sets of the tone values of said second color coordinate system of which said tone values have been proportionally increased, while correlating sets of said first color coordination system and sets of said second color coordination system, and
said color conversion module converts said first image data into said second image data of which said tone values have been proportionally increased, by referencing said proportionally increased color conversion table.
3. An image processing apparatus in accordance with claim 1, wherein the image processing apparatus further comprises a corrected dot volume table that records increased tone values of said second image data of which the tone values have been proportionally increased and corrected dot volume data which is the dot volume data corrected so as to be embarrassed from effects due to the proportional increase of said second image data, with respect to each color of said second color coordinate system, and
said dot volume data conversion module converts said second image data of which the tone values have been proportionally increased into said corrected dot volume data for each of said various type dots with respect to each color of said second color coordinate system, by referencing said corrected dot volume table.
4. An image processing apparatus in accordance with claim 1, wherein said color conversion module further comprises a first image data proportional increase module that increases proportionally the tone values of said first image so that the tone values of said second image data are proportionally increased with the sequence of the tone value relationship between said second image data kept the same within said preset tone range of said second image data, while
said color conversion module converts the proportionally increased first image data into said second image in order to obtain second image data of which said tone values are proportionally increased.
5. An image processing apparatus in accordance with claim 1, wherein said smallest dots are the dots which have the smallest dot size among said various type dots.
6. An image processing apparatus in accordance with claim 1, wherein said smallest dots are the lowest in concentration of colorant among dots for each color of said second color coordinate system.
7. An image processing apparatus in accordance with claim 1, wherein image data expressed by the tone values of each color including at least the three primary colors of light are received as said first image data, and are converted into said dot volume data of each color including at least the three primary colors of ink.
8. An image processing apparatus in accordance with claim 1, said image processing apparatus further comprising:
a color conversion table on which are recorded sets of various tone values of said first color coordinate system and sets of tone values of each color of said second color coordinate system, with these sets correlated to each other, and
a proportionally increased color conversion table generating module that performs a specified conversion on said color conversion table and that generates a proportionally increased color conversion table on which are recorded sets of various tone values of said first color coordinate system and sets of tone values of each color of the second color coordinate system of which said tone values have been proportionally increased, with these sets correlated to each other, wherein
said color conversion module converts said first image data into second image data of which said tone values have been proportionally increased, by referencing said proportionally increased color conversion table.
9. An image processing apparatus in accordance with claim 8, wherein the sets of various tone values of said first color coordinate system which form said proportionally increased color conversion table are different at least in a part from the sets of various tone values of said first color coordinate system which form said color conversion table.
10. An image processing apparatus in accordance with claim 9, wherein said proportionally increased color conversion table records more sets of various tone values of said first color coordinate system than said color conversion table, with the each set correlated to sets of the tone values of each color of the second color coordinate system of which said tone values are proportionally increased.
11. A printing control apparatus that converts image data expressed by sets of various tone values which express a color image into printing data expressed by the dot on-off state of various type dots which express different tone values per respective single dots, and that controls a printing unit by providing said printing data to the printing unit that prints an image by forming said various dots on a printing medium, said printing control apparatus comprising:
a color conversion module that receives first image data expressed by sets of various tone values of a first color coordinate system and converts the first image data into second image data expressed by sets of the tone values of each color which comprises a second color coordinate system; and
a dot volume data conversion module that converts said second image data into said dot volume data relating to the dot formation density for each of the various type dots with respect to each color of said second color coordinate system,
a dot formation judgment module that judges the dot on-off state for each of said various dots with respect to each color of said second color coordinate system based on said dot volume data, and
a printing data output module that outputs as said printing data to said printing unit the judgment results of said dot on-off state,
wherein said color conversion module converts said first image data into second image data which are increased proportionally with the tone value relationship between said second image data kept in the same sequence, when said second image data is at least in a preset tone range where the smallest dots, which express the smallest tone value per respective single dots among the various type dots, are generated, and
said dot volume data conversion module converts said second image data of which said tone value is increased proportionally into said dot volume data which have been corrected to be embarrassed from said proportional increase.
12. An image processing method that converts image data expressed by sets of various tone values which express a color image into dot volume data related to dot formation density of various type dots which express different tone values per respective single dots, said image processing method comprising:
(A) a process of receiving first image data expressed by sets of various tone values of a first color coordinate system and converting the first image data into second image data expressed by sets of the tone values of each color which comprises a second color coordinate system; and
(B) a process of converting said second image data into said dot volume data of said various type dots with respect to each color of said second color coordinate system,
wherein said process (A) converts said first image data into second image data which are increased proportionally with the tone value relationship between said second image data kept in the same sequence, when said second image data is at least in a preset tone range where the smallest dots, which express the smallest tone value per respective single dots among the various type dots, are generated, and
said process (B) converts said second image data of which said tone value is increased proportionally into said dot volume data which have been corrected to be embarrassed from said proportional increase.
13. A recording medium in which a program is recorded in a computer readable manner, said program actualizing a method that converts image data expressed by sets of various tone values which express a color image into dot volume data related to dot formation density of various type dots which express different tone values per respective single dots, said program causing a computer to attain:
(A) a function of receiving first image data expressed by sets of various tone values of a first color coordinate system and converting the first image data into second image data expressed by sets of the tone values of each color which comprises a second color coordinate system; and
(B) a function of converting said second image data into said dot volume data of said various type dots with respect to each color of said second color coordinate system,
wherein said function (A) converts said first image data into second image data which are increased proportionally with the tone value relationship between said second image data kept in the same sequence, when said second image data is at least in a preset tone range where the smallest dots, which express the smallest tone value per respective single dots among the various type dots, are generated, and
said function (B) converts said second image data of which said tone value is increased proportionally into said dot volume data which have been corrected to be embarrassed from said proportional increase.
14. A program for actualizing a method that converts image data expressed by sets of various tone values which express a color image into dot volume data related to dot formation density of various type dots which express different tone values per respective single dots, said program causing a computer to attain:
(A) a function of receiving first image data expressed by sets of various tone values of a first color coordinate system and converting the first image data into second image data expressed by sets of the tone values of each color which comprises a second color coordinate system; and
(B) a function of converting said second image data into said dot volume data of said various type dots with respect to each color of said second color coordinate system.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A computer-implemented method of displaying content, comprising:
displaying an overlay object fixed to a side of a content area;
sending a request for content to a server;
receiving a response from the server; and
displaying content in the overlay object according to the response.
2. A computer-implemented method according to claim 1, wherein the overlay object is displayed according to a set of downloaded instructions.
3. A computer-implemented method according to claim 2, wherein the set of downloaded instructions are distributed through a custom installation.
4. A computer-implemented method according to claim 2, wherein the set of downloaded instructions are distributed through a third party.
5. A computer-implemented method according to claim 2, wherein the set of downloaded instructions are distributed via at least one of a real-time bidding exchange, a publisher network, and a third-party server.
6. A computer-implemented method according to claim 2, wherein the set of downloaded instructions are distributed through an application installed on a user device.
7. A computer-implemented method according to claim 1, wherein the overlay object is a child of the content area.
8. A computer-implemented method according to claim 1, wherein the content area operates on a networked device.
9. A computer-implemented method according to claim 1, wherein the response comprises advertisement content.
10. A computer-implemented method according to claim 9, wherein the advertisement content comprises at least one of a search bar, a textual advertisement, a graphical advertisement, a rich-media advertisement, a video advertisement, and a lead capture form.
11. A computer-implemented method according to claim 9, wherein the advertisement content is displayed in tandem with an advertisement in the content area.
12. A computer-implemented method according to claim 1, wherein the response comprises a decision to display non-advertisement content.
13. A computer-implemented method according to claim 12, wherein the non-advertisement content comprises at least one of a toolbar, real-time content, a widget, a productivity tool, and an interactivity tool.
14. A computer-implemented method according to claim 1, wherein the response comprises a decision to display no content.
15. A computer-implemented method according to claim 1, wherein the response comprises a decision to display advertisements to retarget a user.
16. A computer-implemented method according to claim 1, wherein the response is determined according to an optimization algorithm.
17. A computer-implemented method according to claim 16, wherein the optimization algorithm predicts future click activity using a feedback mechanism.
18. A computer implemented method according to claim 17, wherein the feedback mechanism comprises at least one of contextual attributes, demographic attributes, geographic attributes, and user-specific attributes.
19. A computer-implemented method according to claim 16, wherein the optimization algorithm predicts future click activity using click-through data.
20. A computer implemented method according to claim 19, wherein the click-through data is summarized based on at least one of contextual, demographic, geographic, and user-specific attributes.
21. A computer implemented method according to claim 16, wherein the optimization algorithm predicts future click activity based on user activity.
22. A computer implemented method according to claim 1, wherein the overlay object comprises a customization feature.
23. A non-transitory medium storing computer-executable instructions, wherein the instructions are configured to cause a computer to:
display an overlay object fixed to a side of a content area;
send a request for content to a server;
receive a response from the server; and
display content in the overlay object according to the response.
24. A non-transitory medium according to claim 23, wherein the computer displays the overlay object according to a set of downloaded instructions.
25. A non-transitory medium according to claim 24, wherein the set of downloaded instructions are distributed through a custom installation.
26. A non-transitory medium according to claim 24, wherein the set of downloaded instructions are distributed through a third party.
27. A non-transitory medium according to claim 24, wherein the set of downloaded instructions are distributed via at least one of a real-time bidding exchange, a publisher network, and a third-party server.
28. A non-transitory medium according to claim 24, wherein the set of downloaded instructions are distributed through an application installed on a user device.
29. A non-transitory medium according to claim 23, wherein the overlay object is a child of the content area.
30. A non-transitory medium according to claim 23, wherein the content area operates on a networked device.
31. A non-transitory medium according to claim 23, wherein the response comprises advertisement content.
32. A non-transitory medium according to claim 31, wherein the advertisement content comprises at least one of a search bar, a textual advertisement, a graphical advertisement, a rich-media advertisement, a video advertisement, and a lead capture form.
33. A non-transitory medium according to claim 31, wherein the advertisement content is displayed in tandem with an advertisement in the content area.
34. A non-transitory medium according to claim 23, wherein the response comprises a decision to display non-advertisement content.
35. A non-transitory medium according to claim 34, wherein the non-advertisement content comprises at least one of a toolbar, real-time content, a widget, a productivity tool, and an interactivity tool.
36. A non-transitory medium according to claim 23, wherein the response comprises a decision to display no content.
37. A non-transitory medium according to claim 23, wherein the response comprises a decision to display advertisements to retarget a user.
38. A non-transitory medium according to claim 23, wherein the response is determined according to an optimization algorithm.
39. A non-transitory medium according to claim 38, wherein the optimization algorithm predicts future click activity using a feedback mechanism.
40. A non-transitory medium according to claim 39, wherein the feedback mechanism comprises at least one of contextual attributes, demographic attributes, geographic attributes, and user-specific attributes.
41. A non-transitory medium according to claim 38, wherein the optimization algorithm predicts future click activity using click-through data.
42. A non-transitory medium according to claim 41, wherein the click-through data is summarized based on at least one of contextual, demographic, geographic, and user-specific attributes.
43. A non-transitory medium according to claim 38, wherein the optimization algorithm predicts future click activity based on user activity.
44. A non-transitory medium according to claim 23, where the object area comprises a customization feature.
45. A computer system configured to display content, comprising:
a processor having access to a network; and
a memory responsive to the processor, wherein the memory stores an optimization program adapted to cause the computer system to:
receive an inventory request, comprising a set of activity data; and
send a response to the inventory request, wherein the response is determined according to the set of activity data.
46. A computer system according to claim 45, wherein the response comprises content to be displayed in an overlay object fixed to a side of a content area.
47. A computer system according to claim 45, wherein the response is determined according to a distribution via at least one of a real-time bidding exchange, a publisher network, and a third-party server.
48. A computer system according to claim 45, wherein the response comprises advertisement content.
49. A computer system according to claim 48, wherein the advertisement content comprises at least one of a search bar, a textual advertisement, a graphical advertisement, a rich-media advertisement, a video advertisement, and a lead capture form.
50. A computer system according to claim 48, wherein the advertisement content is displayed in tandem with a second advertisement.
51. A computer system according to claim 45, wherein the response comprises a decision to display non-advertisement content.
52. A computer system according to claim 51, wherein the non-advertisement content comprises at least one of a toolbar, real-time content, a widget, a productivity tool, and an interactivity tool.
53. A computer system according to claim 45, wherein the response comprises a decision to display no content.
54. A computer system according to claim 45, wherein the response comprises a decision to display advertisements to retarget a user.
55. A computer system according to claim 45, wherein the response is determined according to an optimization algorithm.
56. A computer system according to claim 55, wherein the optimization algorithm predicts future click activity using a feedback mechanism.
57. A computer system according to claim 56, wherein the feedback mechanism comprises at least one of contextual attributes, demographic attributes, geographic attributes, and user-specific attributes.
58. A computer system according to claim 55, wherein the optimization algorithm predicts future click activity using click-through data.
59. A computer system according to claim 58, wherein the click-through data is summarized based on at least one of contextual, demographic, geographic, and user-specific attributes.
60. A computer system according to claim 55, wherein the optimization algorithm predicts future click activity based on user activity.
61. A computer system according to claim 55, where in the optimization algorithm predicts future click activity in real time.
62. A computer system according to claim 45, wherein the set of activity data comprises a history of responses to advertisements.
63. A computer system according to claim 46, where the overlay object comprises a customization feature.