Samsung electronics co., ltd. (20240161326). METHOD AND APPARATUS WITH SYMMETRY DETECTION simplified abstract
Contents
- 1 METHOD AND APPARATUS WITH SYMMETRY DETECTION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS WITH SYMMETRY DETECTION - 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
METHOD AND APPARATUS WITH SYMMETRY DETECTION
Organization Name
Inventor(s)
Byungjin Kim of Pohang-si (KR)
METHOD AND APPARATUS WITH SYMMETRY DETECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240161326 titled 'METHOD AND APPARATUS WITH SYMMETRY DETECTION
Simplified Explanation
The patent application describes a method that uses a machine learning model to predict score maps for different pre-set classes of symmetry types in an input image, based on the pixels in the feature map. The method then detects symmetry elements in the input image using the predicted score maps.
- Predicting score maps for pre-set classes of symmetry types using a machine learning model
- Detecting symmetry elements in an input image based on the predicted score maps
Potential Applications
This technology could be applied in various fields such as image processing, computer vision, and pattern recognition.
Problems Solved
This technology helps in automating the detection of symmetry elements in images, which can be a time-consuming task when done manually.
Benefits
The benefits of this technology include improved efficiency, accuracy, and consistency in detecting symmetry elements in images.
Potential Commercial Applications
One potential commercial application of this technology could be in developing software tools for image editing and analysis that incorporate automated symmetry detection features.
Possible Prior Art
One possible prior art could be existing methods for symmetry detection in images using traditional image processing techniques.
What are the limitations of this technology in detecting symmetry elements accurately in complex images?
The accuracy of detecting symmetry elements in complex images may be limited by the quality of the training data used to train the machine learning model.
How does this technology compare to existing methods for symmetry detection in terms of computational efficiency?
This technology may offer improved computational efficiency compared to traditional methods for symmetry detection, as it leverages machine learning models to predict score maps for symmetry types.
Original Abstract Submitted
a method may include predicting, using a machine learning model, score maps for each of a plurality of pre-set classes for predetermined symmetry types, using a plurality of pixels included in the feature map, and detecting a symmetry element of the input image based on the predicted score maps.
