US 12,462,049 B1
Method and an electronic device for decoding information in a multi-dimensional encrypted code
Leigh M. Rothschild, Miami, FL (US)
Filed by Leigh M. Rothschild, Miami, FL (US)
Filed on Aug. 6, 2024, as Appl. No. 18/796,250.
Int. Cl. G06F 21/60 (2013.01); G06F 21/36 (2013.01)
CPC G06F 21/602 (2013.01) [G06F 21/36 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method for decoding information in a multi-dimensional encrypted code, the method comprising:
scanning, by an electronic device, a multi-dimensional encrypted code using an image sensor, wherein the multi-dimensional encrypted code comprises a combination of colors, geometric shapes, and varied spatial arrangements;
determining, by an electronic device, a differentiation between subtle color variations and intricate shape arrangements within the multi-dimensional encrypted code using one or more image processing techniques;
identifying, by an electronic device, at least one color patterns, shape variations, size variations, and spatial distributions within the multi-dimensional encrypted code based on the differentiation between subtle color variations and intricate shape arrangements within the multi-dimensional encrypted code, wherein each of the at least one color patterns are indicative of at least one encoded characters;
translating, by an electronic device, the identified at least one color patterns, shape variations, size variations, and spatial distributions into at least one of a user readable information or a Uniform Resource Locator (URL);
providing, by an electronic device, at least one of the user readable information to a user;
directing, by an electronic device, the user to a web address defined by the Uniform Resource Locator (URL), wherein the multi-dimensional encrypted code comprises time-based color changes to encode dynamic information, allowing the code to represent different data at different time intervals; and
employing, by an electronic device, a neural network trained using machine learning techniques, the neural network being dynamically updated in real time based on newly encountered color patterns and geometrical shapes during scanning, wherein the neural network is configured to continuously improve identification of variations in geometrical shapes and plurality of colors to enhance accuracy, efficiency, data storage and retrieval mechanisms.