Systems and methods for image preprocessing to improve accuracy of object recognition

A system for preprocessing an image for object recognition, the system comprising:

• at least one memory storing instructions;
• and
• at least one processor configured to execute the instructions to perform operations comprising:
• receiving the image having dimensions,
• resizing the image to match input dimensions of a model,
• using the model, detecting a plurality of bounding boxes within the resized image,
• grouping the plurality of bounding boxes into a plurality of groups, wherein bounding boxes within a group have shared areas exceeding an area threshold,
• deriving a first subset of the plurality of bounding boxes by selecting bounding boxes having a highest class confidence scores from at least one group,
• selecting a bounding box from the first subset having a highest score based on area and class confidence score,
• scaling the selected bounding box based on the dimensions of the received image and the input dimensions, and
• outputting the scaled bounding box.

A system for preprocessing an image for object recognition, the system comprising:

• at least one memory storing instructions;
• and
• at least one processor configured to execute the instructions to perform operations comprising:
• receiving the image having dimensions,
• resizing the image to match input dimensions of a model,
• using the model, detecting a plurality of bounding boxes within the resized image,
• deriving a first subset of the plurality of bounding boxes by eliminating bounding boxes having a highest class confidence score below a first class confidence score threshold,
• deriving a second subset of the first subset by eliminating bounding boxes having a highest class confidence score not within a selected class,
• grouping the bounding boxes of the second subset into a plurality of groups, wherein bounding boxes within a group have shared areas exceeding an area threshold,
• deriving a third subset of the grouped bounding boxes by selecting a bounding box having a highest class confidence score from at least one group,
• paring the third subset by eliminating bounding boxes that do not include a center point of the image,
• selecting a bounding box from the pared third subset, the selected bounding box having a highest score based on area and class confidence score,
• scaling the selected bounding box based on the dimensions of the received image and the input dimensions, and
• outputting the scaled bounding box.