Raster image digitization using machine learning techniques

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor of a computing system, cause the computing system to perform operations, the operations comprising:

• receiving a raster image including a plot or graph of measurement data;
• segmenting the raster image into a plurality of segments via a segment detection model, wherein the plurality of segments comprises a plurality of curve segments of the plot or graph;
• extracting one or more curves of the plot or graph based on the plurality of segments via an object extraction model;
• and
• mapping discrete portions of the one or more curves to numerical plot values of the plot or graph to generate a digitized plot or graph.

A computing system, comprising:

• one or more processors;
• and
• a memory system comprising one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations, the operations comprising:
• receiving a raster image including a plot or graph of measurement data;
• segmenting the raster image into a plurality of segments via a segment detection model, wherein the plurality of segments comprises a plurality of curve segments of the plot or graph;
• extracting one or more curves of the plot or graph based on the plurality of segments via an object extraction model;
• and
• mapping discrete portions of the one or more curves to numerical plot values of the plot or graph to generate a digitized plot or graph.