18171921. System and method for increasing a resolution of a three-dimension (3D) image simplified abstract (BANK OF AMERICA CORPORATION)
Contents
- 1 System and method for increasing a resolution of a three-dimension (3D) image
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 System and method for increasing a resolution of a three-dimension (3D) image - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about 3D Image Resolution Enhancement
- 1.13 Original Abstract Submitted
System and method for increasing a resolution of a three-dimension (3D) image
Organization Name
Inventor(s)
Ravindran Padmanaban of Chennai (IN)
Srinivasan Selvaraj of Chennai (IN)
System and method for increasing a resolution of a three-dimension (3D) image - A simplified explanation of the abstract
This abstract first appeared for US patent application 18171921 titled 'System and method for increasing a resolution of a three-dimension (3D) image
Simplified Explanation
The system described in the patent application increases the resolution of a 3D image by determining contours and feature points on the surface of objects within the image.
Key Features and Innovation
- Determines contours of a 3D image
- Identifies feature points on the surface of objects in the image
- Compares mesh image vector with contours to determine intersecting feature points
- Generates structural and textural vectors based on the feature points
- Combines structural and textural vectors to create an enhanced image vector
Potential Applications
This technology could be used in medical imaging for detailed analysis of anatomical structures, in virtual reality and augmented reality applications for enhanced visual experiences, and in industrial design for precise modeling of objects.
Problems Solved
This technology addresses the challenge of increasing the resolution of 3D images without distorting the original features of the objects within the image.
Benefits
- Improved resolution of 3D images
- Enhanced visualization of object surfaces
- Accurate representation of feature points
- Versatile application in various industries
Commercial Applications
- Medical imaging software development
- Virtual reality and augmented reality content creation
- Industrial design and prototyping tools
Prior Art
Readers interested in prior art related to this technology can explore research papers on image processing, computer graphics, and 3D modeling techniques.
Frequently Updated Research
Researchers are continually exploring advancements in image processing algorithms and 3D modeling techniques that could further enhance the resolution and accuracy of 3D images.
Questions about 3D Image Resolution Enhancement
How does this technology improve the visualization of 3D objects?
This technology enhances the visualization by accurately determining feature points on object surfaces and generating an enhanced image vector.
What are the potential applications of this technology beyond image resolution enhancement?
This technology can be applied in medical imaging, virtual reality, augmented reality, and industrial design for various purposes.
Original Abstract Submitted
A system for increasing a resolution of a three-dimension (3D) image determines contours of a 3D image. The system determines a mesh image vector, where the mesh image vector indicates location coordinates of feature points on a surface of an object in the 3D image. The system compares the mesh image vector with each contour. The system determines an intersecting feature point where the mesh image vector meets a contour. The system determines that a baseline dataset includes a first feature point that corresponds to the intersecting feature point. In response, the system generates a structural vector by populating the structural vector with the intersecting feature point. The system determines a color code associated with the intersecting feature point and generates a textural vector by populating the textural vector with the color code. The system generates an image vector by combining the structural vector and the textural vector.
