BACKGROUND

Field

The present disclosure relates to object detection, and more specifically, to systems and methods for detecting edges of objects.

Related Art

With some machine vision applications, detection of edges of objects or boxes moving along a conveyor device, stacked on a pallet, or packed in a container can be important in order to detect gaps and determine the dimensions or type of object. However, related art systems may have difficulty detecting contrast or boundaries between two objects or boxes, between an object and the surrounding environment, or between multiple objects packaged on a single pallet due to color or optical resolution of a camera or other imaging device that is being used. Related art systems relying on a single imaging device may have an increased probability of failing to find or detect the boundaries or edges around the objects. Example implementations of the present invention may address deficiencies in the related art systems.

SUMMARY OF THE DISCLOSURE

Aspects of the present invention may include a method of detecting objects. The method may include generating first edge information from first image data representing an object based on a first mode of image capture, generating second edge information from second image data representing the object based on a second mode of image capture, the second mode being different from the first mode, fusing the first edge information with the second edge information to generate fused edge information, generating an object detection hypothesis based on the fused edge information, and validating the object detection hypothesis based on the fused edge information, the first edge information, and/or the second edge information.

Additional aspects of the present invention may include a non-transitory computer readable medium encoded with instructions for making a computing device execute a method of detecting objects. The method may include generating first edge information from first image data representing an object based on a first mode of image capture, generating second edge information from second image data representing the object based on a second mode of image capture, the second mode being different from the first mode, fusing the first edge information with the second edge information to generate fused edge information, generating an object detection hypothesis based on the fused edge information, and validating the object detection hypothesis based on the fused edge information, the first edge information, and/or the second edge information

Further aspects of the present invention may include a computing system for detecting objects using machine vision. The computing system may include a system interface and a processor communicatively coupled to the system interface. The system interface may be configured for receiving first image data representing an object based on a first mode of image capture and receiving second image data representing the object based on a second mode of image capture, the second mode being different from the first mode. The processor may be configured to perform an object detection method. The method may include generating first edge information from the first image data representing an object based on a first mode of image capture, generating second edge information from the second image data representing an object based on a second mode of image capture, the second mode being different from the first mode, fusing the first edge information with the second edge information to generate fused edge information, generating an object detection hypothesis based on the fused edge information, and validating the object detection hypothesis based on the fused edge information, the first edge information, and/or the second edge information.

Additional aspects of the present invention may include another object detection system for detecting objects using machine vision. The system may include devices configured to capture images of a first image capture mode and capture images of a second image capture mode, devices configured to generate first object edge information from image data collected with a first mode of image capture and generate second object edge information from image data collected with a second mode of image capture, the second mode being different from the first mode, a processor. The processor may be configured to fuse the first object edge information and the second object edge information to generate fused edge information, generate an object detection hypothesis based on the fused edge information, and validate the object detection hypothesis based on the fused edge information, the first object edge information, and the second object edge information.

