18054162. ENHANCING IMAGES IN TEXT DOCUMENTS simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)
Contents
- 1 ENHANCING IMAGES IN TEXT DOCUMENTS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ENHANCING IMAGES IN TEXT DOCUMENTS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
ENHANCING IMAGES IN TEXT DOCUMENTS
Organization Name
INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor(s)
Atul Mene of Morrisville NC (US)
Martin G. Keen of Cary NC (US)
Sarbajit K. Rakshit of Kolkata (IN)
Tushar Agrawal of West Fargo ND (US)
ENHANCING IMAGES IN TEXT DOCUMENTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18054162 titled 'ENHANCING IMAGES IN TEXT DOCUMENTS
Simplified Explanation
The patent application describes a method for enhancing images in documents based on context, using a generative adversarial network (GAN) to selectively emphasize relevant components of the image.
- The method uses document-specific indicators such as nearby text, headings, titles, and tables of content to determine the context in which the image is used.
- The GAN modifies the image according to the context, which may involve erasing or deleting irrelevant components and enhancing relevant components.
- General-purpose images may be retrieved for use in the document and selectively enhanced based on their usage in the document.
Potential Applications
The technology could be applied in various fields such as publishing, advertising, and digital content creation to improve the visual impact of images in documents.
Problems Solved
This technology addresses the issue of static images in documents that may not always be relevant or visually appealing in the context of the surrounding text.
Benefits
The selective enhancement of images based on context can improve the overall readability and visual appeal of documents, making them more engaging for readers.
Potential Commercial Applications
This technology could be utilized by publishing companies, marketing agencies, and online content creators to enhance the quality of images in their materials and attract more viewers.
Possible Prior Art
Prior art in image processing and document editing software may exist, but the specific method of using a GAN to selectively enhance images based on context may be a novel approach.
Unanswered Questions
How does the technology handle complex layouts with multiple images and text elements?
The article does not provide information on how the technology deals with documents containing multiple images and text elements that may have different contexts and relevance levels.
What are the potential limitations or challenges of implementing this technology in real-world applications?
The article does not discuss any potential obstacles or drawbacks that may arise when implementing this technology in practical settings, such as computational resources required or compatibility issues with existing software platforms.
Original Abstract Submitted
Images placed in documents are enhanced based on the context in which the image is used. Context is determined according to document-specific indicators such as nearby text, headings, titles, and tables of content. A generative adversarial network (GAN) modifies the image according to the context to selectively emphasize relevant components of the image, which may include erasing or deleting irrelevant components. Relevant general-purpose images may be retrieved for use in the document and may be selectively enhanced according to usage of the general-purpose image in a given document.
