20240037910. Quantum Method and System for Classifying Images simplified abstract (Multiverse Computing S.L.)

Quantum Method and System for Classifying Images

Organization Name

Multiverse Computing S.L.

Inventor(s)

Victor Onofre of DONOSTIA / SAN SEBASTIÁN (ES)

[[:Category:Daniel Garc�a of DONOSTIA / SAN SEBASTIÁN (ES)|Daniel Garc�a of DONOSTIA / SAN SEBASTIÁN (ES)]][[Category:Daniel Garc�a of DONOSTIA / SAN SEBASTIÁN (ES)]]

[[:Category:Román Or�s of DONOSTIA / SAN SEBASTIÁN (ES)|Román Or�s of DONOSTIA / SAN SEBASTIÁN (ES)]][[Category:Román Or�s of DONOSTIA / SAN SEBASTIÁN (ES)]]

Quantum Method and System for Classifying Images - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240037910 titled 'Quantum Method and System for Classifying Images

Simplified Explanation

The abstract describes a computer-implemented method for classifying images using a quantum trained vision system. The method involves enhancing the contrast of the image and applying dimension reduction to the contrast-enhanced image. The enhanced and dimensionally reduced image is then passed to a quantum trained vision system, which generates a result. The result can be a binary yes/no or true/false indication of whether the image falls into a predefined class or an indication of an object in the image.

• The method involves enhancing the contrast of an image.
• Dimension reduction is applied to the contrast-enhanced image.
• The enhanced and dimensionally reduced image is passed to a quantum trained vision system.
• The quantum trained vision system generates a result.
• The result can be a binary indication of whether the image falls into a predefined class.
• The result can also indicate the presence of an object in the image.

Potential applications of this technology:

• Image classification in various fields such as medical imaging, surveillance, and autonomous vehicles.
• Object detection and recognition in computer vision systems.
• Quality control and inspection in manufacturing processes.
• Facial recognition and biometric identification systems.

Problems solved by this technology:

• Improved accuracy and efficiency in image classification and object detection tasks.
• Overcoming limitations of traditional image processing techniques.
• Handling large and complex datasets.
• Enabling real-time decision-making based on image analysis.

Benefits of this technology:

• Enhanced image contrast improves the visibility of objects and details.
• Dimension reduction reduces the computational complexity and memory requirements.
• Quantum trained vision system offers potential for improved accuracy and performance.
• Enables automated and intelligent systems capable of analyzing and interpreting images.

Original Abstract Submitted

a computer-implemented method of classifying an image using a quantum trained vision system. the method comprises enhancing contrast of the image and applying dimension reduction to the contrast-enhance image. the enhanced contrast and dimensionally reduced image is passed to a quantum trained vision system and a result is generated from the quantum trained vision system. the result could be a simply yes/no or true/false binary result to see whether the image fell into one of several predefined classes. alternatively, the result could be an indication of an object in the image.