METHODS AND SYSTEMS FOR IDENTIFYING A THIN OBJECT

• US 20090169104A1
• Filed: 12/31/2007
• Published: 07/02/2009
• Est. Priority Date: 12/31/2007
• Status: Active Grant

• Current Assignee: Morpho Detection LLC (Smiths Group International Holdings Ltd.)
• Original Assignee: Morpho Detection (Safran SA)
• Inventors: Gable, Todd, Ioannou, Dimitrios
• Granted Patent: US 8,254,676 B2
• Time in Patent Office: Days
• US Class Current: 382/170
• CPC Class Codes: G06V 10/507 Summing image-intensity values; Histogram projection analysis
• CPC Class Codes: G06V 2201/05 Recognition of patterns representing particular kinds of hidden objects, e.g. weapons, explosives, drugs

Abstract

A method for identifying an object within a container is provided. The method includes acquiring image data representing an image, applying a morphological operator to the acquired image data to generate morphed image data, calculating a histogram based on the morphed image data, and classifying the image using the calculated histogram. A classification of the image may be displayed and/or stored in a computer-readable memory.

Claims

1. A method for identifying an object within a container, said method comprising:

acquiring image data representing an image;

applying a morphological operator to the acquired image data to generate morphed image data;

calculating a histogram based on the morphed image data;

classifying the image using the calculated histogram; and

outputting a classification of the image.

2. A method in accordance with claim 1, further comprising segmenting the acquired image data into a plurality of image segments.

3. A method in accordance with claim 2, further comprising labeling each image segment of the plurality of image segments.

4. A method in accordance with claim 1, wherein applying a morphological operator further comprises performing a binary operation on the acquired image data.

5. A method in accordance with claim 1, wherein applying a morphological operator further comprises applying an averaging filter to the acquired image data.

6. A method in accordance with claim 1, wherein applying a morphological operator further comprises assigning an integer value to each image element of the acquired image data.

7. A method in accordance with claim 6, wherein calculating a histogram further comprises calculating a histogram using the assigned integer value of each image element.

8. A method in accordance with claim 1, wherein classifying the image using the calculated histogram further comprises comparing the calculated histogram to a plurality of pre-stored image signatures.

9. A method in accordance with claim 1, wherein classifying the image further comprises classifying the image as one of a bulk object, a thin object, and a random aggregation of image elements.

10. A system for identifying an object within a container, said system comprising:

a data collection system; and

a detection classification system coupled to said data collection system, said detection classification system configured to;

acquire image data representing an image;

apply a morphological operator to the acquired image data to generate morphed image data;

calculate a histogram based on the morphed image data;

classify the image using the calculated histogram; and

output a classification of the image.

11. A system in accordance with claim 10, wherein said detection classification system is further configured to segment the acquired image data into a plurality of image segments.

12. A system in accordance with claim 11, wherein said detection classification system is further configured to label each image segment of the plurality of image segments.

13. A system in accordance with claim 10, wherein said detection classification system is further configured to perform a binary operation on the acquired image data.

14. A system in accordance with claim 10, wherein said detection classification system is further configured to apply an averaging filter to the acquired image data.

15. A system in accordance with claim 10, wherein said detection classification system is further configured to assign an integer value to each image element of the acquired image data.

16. A system in accordance with claim 15, wherein said detection classification system is further configured to calculate a histogram using the assigned integer value of each image element.

17. A system in accordance with claim 10, wherein said detection classification system is further configured to compare the calculated histogram to a plurality of pre-stored image signatures.

18. A system in accordance with claim 10, wherein said detection classification system is further configured to classify the image as one of a bulk object, a thin object, and a random aggregation of image elements.

19. A computer program embodied on a computer-readable medium, said computer program comprising a code segment that configures a processor to:

receive image data representing an image;

apply a morphological operator to the acquired image data to generate morphed image data;

calculate a histogram based on the morphed image data;

classify the image using the calculated histogram; and

output a classification of the image.

20. A computer program in accordance with claim 19, wherein the code segment further configures the processor to:

perform a binary operation on the acquired image data;

apply an averaging filter to the acquired image data;

assign an integer value to each image element of the acquired data; and

calculate a histogram using the assigned integer value of each image element.