18131413. OPTICAL CHARACTER RECOGNITION FOR AUGMENTED IMAGES simplified abstract (Snap Inc.)
Contents
OPTICAL CHARACTER RECOGNITION FOR AUGMENTED IMAGES
Organization Name
Inventor(s)
Kevin Sarabia Dela Rosa of Seattle WA (US)
Byung Eun Jeon of Seattle WA (US)
OPTICAL CHARACTER RECOGNITION FOR AUGMENTED IMAGES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18131413 titled 'OPTICAL CHARACTER RECOGNITION FOR AUGMENTED IMAGES
- Simplified Explanation:**
The patent application describes a system for performing optical character recognition on images that include augmented graphical elements.
- Key Features and Innovation:**
- System accesses images depicting real-world environments with added graphical elements.
- Machine learning model is applied to recognize the graphical elements.
- Standard code representing the recognized graphical element is stored in association with the image.
- Potential Applications:**
This technology could be used in various industries such as:
- Augmented reality
- Image processing
- Document scanning and digitization
- Problems Solved:**
- Efficiently recognizing and storing graphical elements in augmented images.
- Improving accuracy and speed of optical character recognition in complex visual environments.
- Benefits:**
- Enhanced image processing capabilities.
- Streamlined document digitization processes.
- Improved accuracy in recognizing graphical elements in augmented images.
- Commercial Applications:**
Potential commercial uses include:
- Augmented reality applications
- Document management systems
- Image recognition software
- Questions about Optical Character Recognition:**
1. How does the machine learning model improve the accuracy of recognizing graphical elements in augmented images? 2. What are the potential challenges in implementing this technology in real-world applications?
- Frequently Updated Research:**
Stay updated on advancements in machine learning models for optical character recognition and image processing to enhance the system's capabilities.
Original Abstract Submitted
Methods and systems are disclosed for performing optical character recognition on augmented images. The system accesses an image depicting a real-world environment augmented with a graphical element. The system recognizes the graphical element in the image by applying a machine learning (ML) model to the image. The system stores a standard code representing the graphical element that has been recognized in association with the image.
