Method and system of identifying one or more features represented in a plurality of sensor acquired data sets

• US 9,111,169 B2
• Filed: 09/05/2012
• Issued: 08/18/2015
• Est. Priority Date: 09/01/2006
• Status: Active Grant

• Current Assignee: SenSen Networks Group Pty., Ltd.
• Original Assignee: SenSen Networks Pty., Ltd. (SenSen Networks Ltd.)
• Inventors: Challa, Subhash
• Primary Examiner(s): Park, Edward
• Application Number:
  US13/604,536
• Publication Number:
  US 20130004024A1
• Time in Patent Office: 1,077 Days
• Field of Search: 382/190, 382/208, 382/181, 382/155, 382/161, 382/100, 382/105, 382/104
• US Class Current: 1/1
• CPC Class Codes: G06F 18/256 of results relating to different input data, e.g. multimodal recognition
• CPC Class Codes: G06V 10/811 the classifiers operating on different input data, e.g. multi-modal recognition
• CPC Class Codes: G06V 20/625 License plates
• CPC Class Codes: G06V 20/63 Scene text, e.g. street names

Abstract

A method and system for identifying one or more features represented in a plurality of sensor acquired data sets is described. The method and apparatus is particularly useful in automatic license plate recognition applications, where the sensor acquired data sets are data obtained from one or more digital cameras. This is achieved by determining a first probability of the identity of the one or more features (e.g., alphanumeric characters) from a first one of the data sets; determining a second probability of the identity of the one or more features from a second one of the data sets; and, using data fusion techniques, fusing the determined first and second probabilities to provide a fused probability. This fused probability is used to identify the one or more features from data sets.

Claims

1. A computer program product for identifying a vehicle registration number from a plurality of images comprising representations of a vehicle registration plate, the computer program product stored on a non-transitory computer-readable medium and configured to cause a computer to perform steps comprising:

determining a first probability distribution of alphanumeric characters present in a portion of one of the images;

determining a second probability distribution of alphanumeric characters present in a portion of another of the images, the portion of the other of the images corresponding to the portion of the one of the images;

fusing the first and second probability distributions to provide a fused probability distribution of alphanumeric characters in relation to the one and the other images; and

identifying which alphanumeric character is present in the respective portions of the one and the other images by identifying from the fused probability distribution the alphanumeric character having the highest probability of being present.

2. A system for identifying for identifying a vehicle registration number from a plurality of images comprising representations of a vehicle plate, the system comprising:

one or more sensors configured to acquire a plurality of images comprising representations of a vehicle registration plate;

a computer device in communication with the one or more sensors configured to acquire the images from the one or more sensors; and

a calculating device configured to;

determine a first probability distribution of alphanumeric characters present in a portion of one of the images;

determine a second probability distribution of alphanumeric characters present in a portion of another of the images, the portion of the other of the images corresponding to the portion of the one of the images;

fuse the first and second probability distributions to provide a fused probability distribution of alphanumeric characters in relation to the one and the other images; and

identify which alphanumeric character is present in the respective portions of the one and the other images by identifying from the fused probability distribution the alphanumeric character having the highest probability of being present.

3. A method of identifying a vehicle registration number from a plurality of images comprising representations of a vehicle registration plate, the method comprising:

determining a first probability distribution of alphanumeric characters present in a portion of one of the images;

determining a second probability distribution of alphanumeric characters present in a portion of another of the images, the portion of the other of the images corresponding to the portion of the one of the images;

fusing the first and second probability distributions to provide a fused probability distribution of alphanumeric characters in relation to the one and the other images; and

identifying which alphanumeric character is present in the respective portions of the one and the other images by identifying from the fused probability distribution the alphanumeric character having the highest probability of being present.

4. The method of claim 3 further comprising, after the fusing:

determining a third probability distribution of alphanumeric characters present in a portion of a third one of the images; and

fusing the fused probability distribution and the third probability distribution to provide a second fused probability distribution,

wherein the identifying uses the second fused probability.

5. The method of claim 3, wherein when the plate displays a combination of at least two alphanumeric characters, the method is repeated to identify a first one of the two characters and then a second one of the two characters from each of the at least two data sets.

6. The method of claim 3 wherein, prior to determining the first probability, the number of alphanumeric characters present on the plate is determined, and the remainder of the method is performed for each alphanumeric character determined as present on the plate.

7. The method of claim 3, further comprising identifying respective location(s) of the license plate in respective said images by determining third and fourth probably density functions representing the probability of the license plate being in a location in the respective image, fusing the third and fourth probability distributions to provide a fused probability distribution of location, and identifying the location by identifying from the fused probability distribution of location the location having the highest probability of being correct.

8. The method of claim 7 wherein the third and fourth probability distributions are determined using one or more parameters of the following group:

size of a potential representation of the license plate compared to other potential representation(s) of the license plate;

shape of the potential representation of the license plate;

similarities of size and/or shape of the potential representation of the license plate in one of the images compared to the size and/or shape of another potential representation in another of the images; and

the position of the potential representation of the license plate in one of the images relative to the position of another potential representation in another of the images.

9. The method of claim 3 wherein, prior to determining the first probability, the images used in the method are subjected to black and white image thresholding and the probability determinations are performed on the thresholded black and white images.

10. The method of claim 3 implemented by a computer.

11. The method of claim 3, wherein an algorithm selected from the group of algorithms comprising Bayesian Fusion, Distributed Data Fusion, Dempster-Shafer Fusion, Fuzzy Fusion, Random Sets Based Fusion, Voting and Dezert Samaranche Fusion is used in the fusing to fuse the first and second probability distributions.

12. The method of claim 3 further comprising, prior to determining the first probability distribution, determining the number of alphanumeric characters present on the vehicle registration plate, and performing the method for each alphanumeric character present on the vehicle registration plate.