View source for 18511899. Automated Digital Tool Identification from a Rasterized Image simplified abstract (ADOBE INC.)

=Automated Digital Tool Identification from a Rasterized Image=


==Organization Name==

[[:Category:ADOBE INC.|ADOBE INC.]]


[[Category:ADOBE INC.]]

==Inventor(s)==

[[:Category:Matthew David Fisher of San Carlos CA (US)|Matthew David Fisher of San Carlos CA (US)]][[Category:Matthew David Fisher of San Carlos CA (US)]]

[[:Category:Vineet Batra of Pitam Pura (IN)|Vineet Batra of Pitam Pura (IN)]][[Category:Vineet Batra of Pitam Pura (IN)]]

[[:Category:Mrinalini Sardar of Noida (IN)|Mrinalini Sardar of Noida (IN)]][[Category:Mrinalini Sardar of Noida (IN)]]

[[:Category:Ankit Phogat of Noida (IN)|Ankit Phogat of Noida (IN)]][[Category:Ankit Phogat of Noida (IN)]]

==Automated Digital Tool Identification from a Rasterized Image - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18511899 titled 'Automated Digital Tool Identification from a Rasterized Image

==Simplified Explanation==

The visual lens system described in the patent application automatically identifies digital tool parameters to achieve a desired visual appearance in raster image data without user intervention. Here are some key points to explain the innovation:

* The system processes raster image data using a tool region detection network to determine if a digital tool can achieve the visual appearance of each pixel.
* A mask is generated by the network to indicate the usability of the digital tool for each pixel in the image.
* A tool parameter estimation network then generates a probability distribution to estimate discrete parameter configurations that can be applied to the digital tool to achieve the visual appearance.
* An image tool description is created for the parameter configuration and incorporated into an interactive image for the raster image data.
* The image tool description allows for the transfer of the digital tool parameter configuration to different image data.

== Potential Applications ==
The technology described in the patent application could have potential applications in various industries such as graphic design, image editing software, and computer vision systems.

== Problems Solved ==
This technology solves the problem of manually adjusting digital tool parameters to achieve a desired visual appearance in raster image data, saving time and effort for users.

== Benefits ==
The benefits of this technology include automation of the parameter identification process, improved efficiency in achieving desired visual appearances, and enhanced user experience in working with raster image data.

== Potential Commercial Applications ==
One potential commercial application of this technology could be in the development of advanced image editing software that offers automated parameter adjustment for users.

== Possible Prior Art ==
One possible prior art for this technology could be existing image processing algorithms that involve automated parameter estimation for image enhancement.

=== Unanswered Questions ===

=== How does the visual lens system handle complex images with multiple regions that require different tool parameters for visual appearance enhancement? ===
The system likely uses advanced algorithms to analyze and process each region separately, determining the appropriate tool parameters for each based on the visual characteristics of the region.

=== Can the visual lens system adapt to different types of digital tools and their specific parameter requirements? ===
The system is likely designed to be flexible and adaptable, allowing for customization to accommodate various digital tools and their unique parameter configurations.


==Original Abstract Submitted==

A visual lens system is described that identifies, automatically and without user intervention, digital tool parameters for achieving a visual appearance of an image region in raster image data. To do so, the visual lens system processes raster image data using a tool region detection network trained to output a mask indicating whether the digital tool is useable to achieve a visual appearance of each pixel in the raster image data. The mask is then processed by a tool parameter estimation network trained to generate a probability distribution indicating an estimation of discrete parameter configurations applicable to the digital tool to achieve the visual appearance. The visual lens system generates an image tool description for the parameter configuration and incorporates the image tool description into an interactive image for the raster image data. The image tool description enables transfer of the digital tool parameter configuration to different image data.



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