Segment-based pattern matching algorithm

A computer-implemented method for matching a pattern, the method comprising:

• generating a set of model descriptors representative of segment features of a first object captured in a first image including defining a set of model descriptors by determining a location of a midpoint, an orientation angle relative to the x-axis, and a link between endpoints for each model segment;
• generating a set of query descriptors representative of segment features of a second object captured in a second image;
• selecting a first model segment to align with the query segments to determine if any of the query segments correspond with the first model segment based on respective model descriptors and query descriptors;
• generating a hypothesis by computing a transformation to match the selected first model descriptor with a query descriptor;
• validating the hypothesis by performing a model fitting algorithm when comparing other transformed model descriptors with other query descriptors;
• and
• based on a consensus value from the model fitting algorithm, determining whether a pattern match exists between the first and second images.

An imaging system, comprising:

• an imaging camera;
• a processing unit in communication with said imaging camera, and configured to:
• generate a set of model descriptors representative of segment features of a first object captured in a first image and define a set of model descriptors by determining a location of a midpoint, an orientation angle relative to the x-axis, and a link between endpoints for each model segment;
• generate a set of query descriptors from a second object captured in a second image;
• select a first model segment to align with the query segments to determine if any of the query segments correspond with the first model segment based on respective model descriptors and query descriptors;
• generate a hypothesis by computing a transformation to match the selected first model descriptor with a query descriptor;
• validate the hypothesis by performing a model fitting algorithm when comparing other transformed model descriptors with other query descriptors;
• and
• based on a consensus value from the model fitting algorithm, determine whether a pattern match exists between the first and second images.