Fractal features used with nearest neighbor clustering for identifying clutter in sonar images
First Claim
1. A method of identifying clutter in an image represented by a two-dimensional array of pixel intensities, said method comprising the steps of:
- applying a detection scheme to said two-dimensional array to identify portions of said image having a signal-to-noise ratio greater than a given threshold, wherein each of said portions is centered at a position in said image that is represented by a two-dimensional coordinate pair generated by said detection scheme;
applying a classification scheme to each of said portions to generate fractal feature values associated therewith, wherein each of said portions is classified as being one of a target and non-target based on said fractal feature values associated with each of said portions;
assigning each of said portions to a group based on a distance from said position of each of said portions to another of said portions that is its nearest neighbor; and
performing at least one test for each said group using said fractal feature values associated with each of said portions in each of said groups, wherein a failure of any of said at least one test by any one of each said group identifies each of said portions associated with said any one of each said group as clutter in said image.
1 Assignment
0 Petitions
Accused Products
Abstract
A method is presented for identifying clutter in an image such as a sonar age. A detection scheme identifies portions of the image having a signal-to-noise ratio greater than a given threshold. A classification scheme is then applied to each such portion to generate fractal feature values associated therewith in order to classify the portion as a target or non-target. For clutter identification, each portion is assigned to a group based on a distance from the position of each portion to another of the portions that is its nearest neighbor. A series of tests are then performed for each group using the fractal feature values associated with each portion in each group. A failure of any of the series of tests by a group identifies each portion associated with that group as clutter in the image.
-
Citations
16 Claims
-
1. A method of identifying clutter in an image represented by a two-dimensional array of pixel intensities, said method comprising the steps of:
-
applying a detection scheme to said two-dimensional array to identify portions of said image having a signal-to-noise ratio greater than a given threshold, wherein each of said portions is centered at a position in said image that is represented by a two-dimensional coordinate pair generated by said detection scheme; applying a classification scheme to each of said portions to generate fractal feature values associated therewith, wherein each of said portions is classified as being one of a target and non-target based on said fractal feature values associated with each of said portions; assigning each of said portions to a group based on a distance from said position of each of said portions to another of said portions that is its nearest neighbor; and performing at least one test for each said group using said fractal feature values associated with each of said portions in each of said groups, wherein a failure of any of said at least one test by any one of each said group identifies each of said portions associated with said any one of each said group as clutter in said image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
-
-
9. A method of identifying clutter in a sonar image comprising the steps of:
-
providing a two-dimensional array of pixel intensities representative of said sonar image; normalizing said pixel intensities; applying a detection scheme to said two-dimensional array to identify portions of said sonar image having a signal-to-noise ratio greater than a given threshold, wherein each of said portions is centered at a position in said image that is represented by a two-dimensional coordinate pair generated by said detection scheme; applying a classification scheme to each of said portions to generate fractal feature values associated therewith, wherein each of said portions is classified as being one of a target and non-target based on said fractal feature values associated with each of said portions; assigning each of said portions to a group based on a distance from said position of each of said portions to another of said portions that is its nearest neighbor; and performing a series of tests for each said group using said fractal feature values associated with each of said portions in each of said groups, wherein a failure of any of said series of tests by any one of each said group identifies each of said portions associated with said any one of each said group as clutter in said sonar image. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
-
Specification