Method and apparatus of automated optical container code recognition with positional identification for a transfer container crane

• US 20060153455A1
• Filed: 03/13/2006
• Published: 07/13/2006
• Est. Priority Date: 08/02/2001
• Status: Active Grant

• Current Assignee: HKI Systems and Service LLC
• Original Assignee: Paceco Corporation (Mitsui E&S Company Limited)
• Inventors: Takehara, Toru, King, Maxwell W., Chung, Chingyei
• Granted Patent: US 7,308,114 B2
• Time in Patent Office: Days
• US Class Current: 382/181
• CPC Class Codes: B66C 19/007 for containers
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G06V 20/62 Text, e.g. of license plates, overlay texts or captions on TV images
• CPC Class Codes: G06V 30/10 Character recognition

Abstract

A method and system providing a transfer container crane with container code recognition of a container identified by a container code to a container inventory management system is disclosed. The system and method are capable of performing these tasks without the use of non-standard container tagging.

Claims

1. A method providing container code recognition from a transfer container crane of a container identified by a container code to a container inventory management system, comprising the steps of:

generating an optical characteristic of said container code based upon at least one video imaging device mechanically coupled to said transfer container crane;

generating a positional identification of said container; and

sending said optical characteristic of said container code and said positional identification of said container to said container inventory management system.

2. The method of claim 1,

wherein the step generating said optical characteristic of said container code is comprised of the steps of:

acquiring at least one container code image of a container representation of said container code imaged from said video imaging device; and

applying an optical character recognition process to said container code image to create an estimated container code;

acquiring a first container code image from said video imaging device of said container representation of said container code; and

compressing said first container code image to create said container code image;

wherein said video imaging device belongs to a collection comprising at least a video camera, a digital video camera, and a charged coupled array.

3. The method of claim 2,

wherein the step acquiring said container code image is further comprised of the at least one member of the collection comprising the steps of:

selecting a first of at least two of said video imaging devices; and

acquiring said container code image from said first video imaging device of said container representation of said container code.

4. The method of claim 2,

wherein the step generating said optical characteristic of said container code is comprised of the step of:

processing said first container code image to create said container code image.

5. The method of claim 4, further comprised of the step of:

receiving a modified container code image request; and

wherein the step processing said first container code image is further comprised of the step of;

processing said first container code image based upon said modified container code image request to create said container code image.

6. The method of claim 1,

wherein the step generating said positional identification of said container is further comprised of at least one member of the collection comprising the steps of:

generating a loading-operation designation for said container;

generating a storage-location designation for said container; and

generating a terminal location for said transfer container crane.

7. The method of claim 6,

wherein the step generating said loading-operation is further comprised of at least one member of the collection comprising the steps of:

receiving a locking indication from a programmable logic controller within said transfer container crane; and

determining said locking indication from a relay network within said transfer container crane;

wherein the step generating said loading-operation is further comprised of at least one member of the collection comprising the steps of;

determining a container hoist position based upon sensing a gray-coded hoist shaft in said transfer container crane; and

determining said container hoist position based upon sensing an ultrasonic transponder; and

wherein the step generating said loading-operation is further comprised of the step of;

generating said loading-operation designation based upon at least one member of the collection comprising said locking signal indication and said container hoist position.

8. The method of claim 6,

wherein the step generating said storage-location designation is further comprised the step of:

deriving said storage-location designation for said container at least in part from said terminal location for said transfer container crane; and

wherein the step generating said terminal location for said transfer container crane is further comprised of the step of;

receiving a location reading from a Global Positioning System (GPS) receiver to create at least in part said terminal location for said transfer container crane;

wherein said GPS receiver is mechanically coupled with said transfer container crane.

9. The method of claim 1,

wherein the step sending said optical characteristic and said positional identification, is comprised of the steps of:

sending a packet from a network to create a received packet; and

creating said packet from at least part of at least one member of a sending-data collection;

wherein said sending-data collection is comprised of said optical characteristic of said container code and said positional identification of said container;

wherein said network employs at least one member of a physical transport collection in communicating from said transfer container crane to container inventory management system;

wherein said physical transport collection is comprised of at least one wireline physical transport layer and at least one wireless physical transport layer.

10. The method of claim 9,

wherein the step sending said optical characteristic and said positional identification, is comprised of at least one member of the collection comprising the steps of:

writing said optical characteristic of said container code and said positional identification of said container to a removable non-volatile memory;

writing at least one member of said sending-data collection to a file contained in said removable non-volatile memory; and

writing at least one member of said sending-data collection to a record contained in said removable non-volatile memory.

11. A program system implementing the method of claim 1 by controlling a computer through a collection of program steps implementing the steps of claim 31,

wherein said program steps reside in a memory accessibly coupled with said computer.

12. A system implementing the method of claim 1, comprising a means implementing each of the steps of claim 1.

13. The system of claim 12,

wherein at least one of said means of claim 12 is comprised of at least one member of the collection comprising:

an instruction processor, an inferential processor, a finite state machine, and a memory;

wherein said instruction processor includes at least one member of the collection comprising;

a Single Instruction Single Datapath (SISD) processor, a Single Instruction Multiple Datapath (SIMD) processor, a Multiple Instruction Single Datapath (MISD) processor, a Multiple Instruction Multiple Datapath (MIMD) processor, a Complex Instruction Set Computer (CISC), a Reduced Instruction Set Computer (RISC) and a Very Long Instruction Word (VLIW) computer;

wherein said inferential processor includes at least one member of the collection comprising;

a rule-based inferential processor, a constraint-based inferential processor, and a fuzzy logic engine;

wherein said finite state machine includes at least one member of the collection comprising;

at least part of a programmable logic device, at least part of an application specific integrated circuit;

wherein said programmable logic device includes at least one member of the collection comprising;

a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a Complex Programmable Logic Array (CPLA);

wherein said memory includes at least one member of the collection comprising;

a volatile memory and a non-volatile memory;

wherein said non-volatile memory includes at least one member of the collection comprising;

a writeable non-volatile memory and a Read Only Memory (ROM);

wherein said writeable non-volatile memory includes at least one member of the collection comprising;

an electro-magnetically interfaced non-volatile memory and an optically interfaced non-volatile memory.