Difference of sum filters for texture classification

• US 20070160308A1
• Filed: 01/11/2006
• Published: 07/12/2007
• Est. Priority Date: 01/11/2006
• Status: Abandoned Application

• Current Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Inventors: Jones, Michael, Guo, Guodong
• Application Number:
  US11/329,791
• Publication Number:
  US 20070160308A1
• Time in Patent Office: Days
• US Class Current: 382/260
• CPC Class Codes: G06V 40/193 Preprocessing; Feature extraction

Abstract

A method for filtering pixels is described. Filters including adjacent regions of pixels are defined and operators are associated with the regions. The operators are summation and subtraction operators. The filters have even and odd symmetry about a central axis. A total intensity value according to the application of the filter is determined. The total intensity value is binarized.

Claims

1. A method for filtering pixel intensities in an image, comprising:

defining a set of adjacent regions of pixels in an image as a filter, each pixel having an intensity value;

associating an operator with each region in the set;

applying each operator to the intensities in each corresponding region to obtain a total intensity value for the set of regions;

thresholding the total intensity value to obtain a binarized intensity value as a single bit representing a texture of the region.

2. The method of claim 1, in which the regions are rectangular.

3. The method of claim 1, further comprising:

applying the filter repeatedly to filter all pixels in the image, each application producing a corresponding single bit; and

combining the single bits into a feature vector representing the texture of the entire image.

4. The method of claim 1, in which there are an even number of regions.

5. The method of claim 1, in which there are an odd number of regions.

6. The method of claim 1, in which the operators are summation and subtraction.

7. The method of claim 1, in which the filter is symmetric about a central axis of the filter.

8. The method of claim 7, in which the filter has an even symmetry about the central axis.

9. The method of claim 7, in which the filter has an odd symmetry about the central axis.

10. The method of claim 1, in which the binarized intensity value is one if the total intensity value is positive, and zero otherwise.

11. The method of claim 1, in which the image is an integral image.

12. The method of claim 1, further comprising:

defining a set of filters, the set of filters including pairs of filters; and

applying each pair of filters in the set of filters to all pixels in the image, each filter in the pair being applied to a same region of pixels.

13. The method of claim 12, in which the filters in each pair of filters are of a same size.

14. The method of claim 13, in which the pairs of filters each include a first filter with an even symmetry and a second filter with an odd symmetry

15. The method of claim 14, in which the set of filters includes four pairs of filters, and in which a size of a first pair of filters is 12×

8 pixels, a size of a second pair of filters is 24×

8 pixels, a size of a third pair of filters is 36×

8 pixels, and a size of a fourth pair of filters is 48×

8 pixels