Quantum Method and System for Classifying Images

Organization Name

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.

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