System and method for object identification

• US 20050058350A1
• Filed: 09/15/2004
• Published: 03/17/2005
• Est. Priority Date: 09/15/2003
• Status: Abandoned Application

• Current Assignee: Lockheed Martin Corporation (Martin Marietta Corporation)
• Original Assignee: Lockheed Martin Corporation (Martin Marietta Corporation)
• Inventors: Fang, Zhiwei (Henry) W., Dugan, Peter J., Ouellette, Patrick, Riess, Michael J.
• Application Number:
  US10/941,660
• Publication Number:
  US 20050058350A1
• Time in Patent Office: Days
• US Class Current: 382/224
• CPC Class Codes: G06V 10/242 by image rotation, e.g. by 90 degrees
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]
• CPC Class Codes: G07B 2017/00685 Measuring the dimensions of mailpieces

Abstract

Methods for object recognition and systems that implement the methods. In one embodiment, the method of this invention for processing and identifying images includes two steps. In the first step, object profile characteristics are obtained. In the second step, object profile characteristics are utilized to determine object type and orientation. A system that implements the method of this invention is also disclosed.

Claims

1. A method for recognizing objects, the method comprising the steps of:

acquiring a plurality of one dimensional images from an object;

obtaining object features for at least one of the plurality of one dimensional images; and

,

classifying the object, utilizing the object features, as belonging to a predetermined object class;

whereby the object is recognized as belonging to the predetermined object class.

2. The method of claim 1 wherein the step of obtaining object features comprises the step of one-dimensionally processing at least one of the plurality of one dimensional images.

3. The method of claim 1 wherein the step of obtaining object features comprises the steps of:

substantially removing noise from at least one of the plurality of one dimensional images;

extracting features from at least one of the plurality of one dimensional substantially noise removed images; and

processing the extracted features.

4. The method of claim 3 further comprising the step of:

determining region of interest data from the extracted features.

5. The method of claim 1 further comprising the step of:

pre-processing the acquired plurality of one dimensional images.

6. The method of claim 3 wherein the step of processing the extracted features comprises the steps of:

processing the extracted features applying coarse detection; and

,

finely detecting the coarsely detected features.

7. The method of claim 3 wherein the step of substantially removing noise comprises the step of:

filtering the at least one of the plurality of one dimensional images with a median-type filter.

8. The method of claim 3 wherein the step of processing the extracted features comprises the step of:

applying contrast and threshold detection to the extracted features.

9. The method of claim 1 wherein the step of classifying the object comprises the step of:

obtaining a confidence rating for the classification of the object features.

10. The method of claim 1 wherein the step of classifying the object comprises the step of obtaining an orientation for the object.

11. The method of claim 1 wherein the step of classifying the object comprises the step of utilizing a minimum distance classifier.

12. The method of claim 1 wherein the step of classifying the object comprises the steps of:

obtaining a coarse classification; and

refining the coarse classification.

13. A method for recognizing objects, the method comprising the steps of:

acquiring a plurality of one dimensional images from an object;

obtaining object features for at least one of the plurality of one dimensional images;

classifying the object according to object type, utilizing the object features in the classification; and

,

detecting object orientation from the object type and the object profile coordinates;

whereby the object is recognized by classifying the object according to object type and detecting object orientation.

14. The method of claim 13 wherein the step of obtaining object features comprises the step of one-dimensionally processing at least one of the plurality of one dimensional images.

15. The method of claim 13 wherein the step of obtaining object features comprises the steps of:

obtaining estimated length data;

obtaining an array of height data;

obtaining a plurality of arrays of length data utilizing the estimated length data and the array of height data; and

,

filtering each one of the arrays of length data.

16. The method of claim 15 wherein the step of filtering each one of the arrays comprises the step of:

filtering each one of the arrays of length data with a median-type filter.

17. The method of claim 13 wherein the object types are container types.

18. The method of claim 13 wherein the step of classifying the object comprises the steps of:

obtaining a coarse classification; and

refining the coarse classification.

19. A system for recognizing objects comprising:

means for acquiring a plurality of one dimensional images from an object;

at least one processor capable of receiving the plurality of one dimensional images; and

,

at least one computer readable memory, having computer readable code embodied therein, the computer readable code capable of causing the at least one processor to;

obtain at least one object feature for at least one of the plurality of one dimensional images;

classify the object according to object type, classification being obtained from the at least one object feature; and

,

detect object orientation from the object type and the at least one object feature;

whereby the object is recognized by classification according to object type and detection of object orientation.

20. The system of claim 19 wherein, in obtaining object features, the computer readable code is capable of causing the at least one processor to:

obtain estimated length data;

obtain an array of height data;

obtain a plurality of arrays of length data utilizing the estimated length data and the array of height data; and

,

filter each one of the arrays of length data.

21. The system of claim 19 wherein, in classifying the object, the computer readable code is capable of causing the at least one processor to:

obtain a coarse classification; and

refine the coarse classification.

22. A computer program product comprising:

a computer usable medium having computer readable code embodied therein, the computer readable code capable of causing a computer system to;

obtain at least one object feature for at least one of the plurality of one dimensional images;

classify the object according to object type, classification being obtained from the at least one object feature; and

,

detect object orientation from the object type and the at least one object feature.

23. The computer program product of claim 22 wherein, in obtaining the at least one object feature, the computer readable code is capable of causing the computer system to:

obtain estimated length data;

obtain an array of height data;

obtain a plurality of arrays of length data utilizing the estimated length data and the array of height data; and

,

filter each one of the arrays of length data.

24. The computer program product of claim 22 wherein, in classifying the object, the computer readable code is capable of causing the computer system to:

obtain a coarse classification; and

refine the coarse classification.