17456422. RADIAL SUMMATION PREPROCESSING FOR IMAGE CLASSIFICATION simplified abstract (International Business Machines Corporation)
RADIAL SUMMATION PREPROCESSING FOR IMAGE CLASSIFICATION
Organization Name
International Business Machines Corporation
Inventor(s)
Sebastien Gilbert of Granby (CA)
RADIAL SUMMATION PREPROCESSING FOR IMAGE CLASSIFICATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 17456422 titled 'RADIAL SUMMATION PREPROCESSING FOR IMAGE CLASSIFICATION
Simplified Explanation
The abstract of this patent application describes a method, computer program product, and computer system for classifying an image using a convolutional neural network (CNN). The method involves receiving an image, performing a radial summation on the image to generate a radially summed image, and inputting this radially summed image into the CNN for image classification.
- The method involves classifying images using a convolutional neural network.
- The image is processed by performing a radial summation, which involves summing the pixel values along radial lines originating from the center of the image.
- The resulting radially summed image is then fed into the CNN for classification.
Potential Applications
- Image recognition and classification tasks in various fields such as computer vision, robotics, and autonomous vehicles.
- Medical imaging analysis for diagnosing diseases or identifying abnormalities.
- Object detection and tracking in surveillance systems or video analysis.
Problems Solved
- Efficiently classifying images using a convolutional neural network.
- Enhancing the performance of image classification algorithms by incorporating radial summation preprocessing.
- Addressing the challenges of image recognition and classification tasks in complex and diverse datasets.
Benefits
- Improved accuracy and efficiency in image classification tasks.
- Robustness to variations in image orientation or rotation.
- Potential for faster processing and reduced computational requirements compared to traditional CNN approaches.
Original Abstract Submitted
A method, a computer program product, and a computer system classify an image with a convolutional neural network. The method receiving an image. The method includes performing a radial summation on the image to generate a radially summed image. The method includes inputting the radially summed image into the CNN to perform an image classification.
