Method for identifying marked images based at least in part on frequency domain coefficient differences
AssigneeNew Jersey Institute of Technology
InventorsYun-Qing Shi, ChunHua Chen
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Abstract
Briefly, in accordance with one embodiment, a method of identifying marked images based at least in part on frequency domain coefficient differences is disclosed.
Claims27
A method of training an image classification process comprising:
- forming at least one coefficient difference array based at least in part a frequency domain representation of the image;
- thresholding the at least one coefficient difference array;
- and
- training an analysis of variance process using the thresholded at least one coefficient difference array.
A method of classifying an image comprising:
- applying a trained analysis of variance process to said image;
- and
- classifying said image based at least in part on a value obtained from application of the trained analysis of variance process.
An article comprising:
- a storage medium having stored thereon instructions that if executed result in performance of a method of training an image classification process as follows:
- forming at least one coefficient difference array based at least in part a frequency domain representation of the image;
- thresholding the at least one coefficient difference array;
- and
- training an analysis of variance process using the thresholded at least one coefficient difference array.
An article comprising:
- a storage medium having stored thereon instructions that if executed results in performance of a method of classifying an image comprising:
- applying a trained analysis of variance process to said image;
- and
- classifying said image based at least in part on a value obtained from application of the trained analysis of variance process.
The article of claim 24, wherein said instructions if executed further resulting in said trained SVM process being based at least in part on coefficient difference arrays.
An apparatus comprising:
- means for forming at least one coefficient difference array based at least in part a frequency domain representation of the image;
- means for thresholding the at least one coefficient difference array;
- and
- means for training an analysis of variance process using the thresholded at least one coefficient difference array.
The apparatus of claim 26, wherein said means for training an analysis of variance process comprises means for training an SVM process.
An apparatus comprising:
- means for applying a trained analysis of variance process to an image;
- and
- means for classifying said image based at least in part on the value obtained from application of the trained analysis of variance process.
Dependencies are inferred from the claim text.