17932478. DETECTING AND RECOVERING PATTERNS IN DIGITAL RASTER IMAGES simplified abstract (ADOBE INC.)
Contents
- 1 DETECTING AND RECOVERING PATTERNS IN DIGITAL RASTER IMAGES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DETECTING AND RECOVERING PATTERNS IN DIGITAL RASTER IMAGES - 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 Unanswered Questions
- 1.11 Original Abstract Submitted
DETECTING AND RECOVERING PATTERNS IN DIGITAL RASTER IMAGES
Organization Name
Inventor(s)
Vineet Agarwal of Guwahati (IN)
Matthew Fisher of San Francisco CA (US)
DETECTING AND RECOVERING PATTERNS IN DIGITAL RASTER IMAGES - A simplified explanation of the abstract
This abstract first appeared for US patent application 17932478 titled 'DETECTING AND RECOVERING PATTERNS IN DIGITAL RASTER IMAGES
Simplified Explanation
The disclosed system automatically detects and reconstructs patterns in digital images by comparing neighborhood descriptors of pixels, utilizing non-maximum suppression to reduce the set of similar pixels, determining pattern cells within the image, and modifying boundaries to include pattern objects.
- The system compares neighborhood descriptors of pixels to identify structurally similar pixels in digital images.
- Non-maximum suppression is used to reduce the set of similar pixels to collinear pixels within the image.
- The system determines if a group of similar pixels define the boundaries of a pattern cell forming a rectangular grid pattern.
- Boundaries of detected pattern cells are modified to include pattern objects via a sliding window corresponding to the pattern cell.
Potential Applications
This technology can be applied in various fields such as image processing, computer vision, pattern recognition, and machine learning.
Problems Solved
1. Automatic detection and reconstruction of patterns in digital images. 2. Efficient reduction of similar pixels to collinear pixels for pattern recognition.
Benefits
1. Improved accuracy in pattern detection and reconstruction. 2. Time-saving in analyzing digital images for patterns. 3. Enhanced efficiency in pattern recognition tasks.
Potential Commercial Applications
Optical character recognition (OCR) software, image editing tools, security systems for pattern recognition, and quality control in manufacturing processes can benefit from this technology.
Possible Prior Art
One possible prior art could be the use of edge detection algorithms in image processing to identify patterns in digital images.
Unanswered Questions
How does the system handle noise or variations in the digital images that may affect pattern detection accuracy?
The system may need to incorporate noise reduction techniques or adaptive algorithms to account for variations in the images.
Can the system detect and reconstruct complex patterns beyond rectangular grid patterns?
Further research and development may be needed to enhance the system's capabilities in detecting and reconstructing more intricate patterns in digital images.
Original Abstract Submitted
Methods, systems, and non-transitory computer readable storage media are disclosed for automatically detecting and reconstructing patterns in digital images. The disclosed system determines structurally similar pixels of a digital image by comparing neighborhood descriptors that include the structural context for neighborhoods of the pixels. In response to identify structurally similar pixels of a digital image, the disclosed system utilizes non-maximum suppression to reduce the set of structurally similar pixels to collinear pixels within the digital image. Additionally, the disclosed system determines whether a group of structurally similar pixels define the boundaries of a pattern cell that forms a rectangular grid pattern within the digital image. The disclosed system also modifies a boundary of a detected pattern cell to include a human-perceived pattern object via a sliding window corresponding to the pattern cell.
