Min Chang - Glenview IL, US Tong Shen - Lake Bluff IL, US Tawakol El-Shourbagy - Wilmette IL, US
International Classification:
B65D039/04 B65D047/44
US Classification:
215/247000, 422/102000
Abstract:
A closure for a container, e.g., a tube, for a sample, e.g., a biological sample. The closure comprises a seal and an adapter to mount the seal onto the container. In one embodiment, the adapter is a cap that is inserted over the mouth of the container. The adapter is typically cylindrical in shape and is characterized by having a circular top with a cylindrical side wall projecting from the top. The top of the adapter has an opening formed therein. The opening generally surrounds the axis of the cylindrically-shaped adapter. The opening has dimensions sufficient to accommodate a sampling device for obtaining access to the contents of the container. The seal depends from the surface of the top of the cap that faces the interior of the container. The seal has a peripheral portion enclosing an interior portion. The peripheral portion has a side wall and a bottom wall. The seal is preferably frusto-conical in shape, with the larger end of the seal adjacent to the top of the adapter and the smaller end of the seal facing the interior of the container. In this preferred embodiment, the seal is attached to the adapter by means of a flange that surrounds the larger end of the seal. An opening for allowing a sampling device to gain access to the contents of the container is formed either in the bottom wall of the seal or in the side wall of the seal at a position close to the bottom wall of the seal.
Hierarchical Systems And Methods For Automatic Container Type Recognition From Images
- Lincolnshire IL, US Tong Shen - Buffalo Grove IL, US Santiago Romero - Mount Airy MD, US
International Classification:
G06K 9/00 G06K 9/40
Abstract:
Hierarchical systems and methods for automatic container type recognition from images are disclosed herein. An example embodiment includes a system for image analysis, comprising: a container recognition component; a character recognition component; and a 3D point cloud component; wherein the container recognition component is configured to receive an image and produce one of three outputs based on analysis of the image such that the output corresponds to either a container is identified, further analysis is performed by the character recognition component, or further analysis is performed by the 3D point cloud component.