Integrated approach to brightness and contrast normalization in appearance-based object detection

1. A method for brightness and contrast normalization in appearance-based object detection, the method comprising:

extracting a plurality of training images;

finding eigenimages corresponding to the training images;

receiving an input image;

forming a projection equation responsive to the eigenimages by adding a scaling and a shift to image intensity and simultaneously solving for intensity normalization parameters;

computing projected and normalized images;

computing an error-of-fit of the projected and normalized images;

thresholding the error-of-fit; and

determining object positions in accordance with the thresholded error-of-fit,

wherein finding eigenimages comprises:

sub-sampling the training images;

forming training images of coarse resolution in accordance with the sub-sampled images;

computing eigenimages corresponding to the training images of coarse resolution;

interpolating the eigenimages for coarse resolution;

performing orthonormalization on the interpolated images by singular value decomposition; and

providing pseudo-eigenimages corresponding to the orthonormalized images for a finer resolution.

2. A method as defined in claim 1 wherein at least one of said plurality of training images and said input image comprises a single-photon emission computed tomography image.

3. A method as defined in claim 1 wherein the computed error-of-fit is represented by a score image.

4. A method for brightness and contrast normalization in appearance-based obiect detection, the method comprising:

extracting a plurality of training images;

finding eigenimages corresponding to the training images;

receiving an input image;

forming a projection equation responsive to the eigenimages by adding a scaling and a shift to image intensity and simultaneously solving for intensity normalization parameters;

computing projected and normalized images;

computing an error-of-fit of the projected and normalized images;

thresholding the error-of-fit; and

determining obiect positions in accordance with the thresholded error-of-fit,

further comprising forming eigenimages for multiresolution, including:

sub-sampling a plurality of training images;

forming training images of coarse resolution in accordance with the sub-sampled images;

computing coarse eigenimages corresponding to the training images of coarse resolution;

interpolating the coarse eigenimages for a finer resolution;

orthonormalizing the interpolated images; and

providing pseudo-eigenimages corresponding to the orthonormalized images for a finer resolution,

wherein the pseudo-eigenimages are formed with a projection equation responsive to the coarse eigenimages by adding a scaling and a shift to image intensity.

5. A method as defined in claim 4 wherein orthonormalizing the interpolated images comprises performing a singular value decomposition.

6. A system for brightness and contrast normalization in appearance-based object detection, the system comprising:

extraction means for extracting a plurality of training images;

finding means for finding eigenimages corresponding to the training images;

receiving means for receiving an input image;

forming/solving means for forming a projection equation responsive to the eigenimages by adding a scaling and a shift to image intensity and simultaneously solving for intensity normalization parameters;

computing means for computing projected and normalized images;

fitting means for computing an error-of-fit of the projected and normalized images;

thresholding means for thresholding the error-of-fit; and

determining means for determining object positions in accordance with the thresholded error-of-fit,

wherein said finding means comprises:

sub-sampling means for sub-sampling the training images;

training means for forming training images of coarse resolution in accordance with the sub-sampled images;

eigenimaging means for computing eigenimages corresponding to the training images of coarse resolution;

interpolating means for interpolating the eigenimages for coarse resolution;

orthonormalization means for performing orthonormalization on the interpolated images by singular value decomposition; and

pseudo-eigenimaging means for providing pseudo-eigenimages corresponding to the orthonormalized images for a finer resolution.

7. A system as defined in claim 6 wherein at least one of said plurality of training images and said input image comprises a single-photon emission computed tomography image.

8. A system as defined in claim 6 wherein the computed error-of-fit is represented by a score image.

9. A system for brightness and contrast normalization in appearance-based object detection, the system comprising:

extraction means for extracting a plurality of training images;

finding means for finding eigenimages corresponding to the training images;

receiving means for receiving an input image;

forming/solving means for forming a projection equation responsive to the eigenimages by adding a scaling and a shift to image intensity and simultaneously solving for intensity normalization parameters;

computing means for computing projected and normalized images;

fitting means for computing an error-of-fit of the projected and normalized images;

thresholding means for thresholding the error-of-fit; and

determining means for determining object positions in accordance with the thresholded error-of-fit;

means for forming eigenimages for multiresolution, including:

sub-sampling means for sub-sampling a plurality of training images;

training means for forming training images of coarse resolution in accordance with the sub-sampled images;

eigenimaging means for computing coarse eigenimages corresponding to the training images of coarse resolution;

interpolating means for interpolating the coarse eigenimages for a finer resolution;

orthonormalizing means for orthonormalizing the interpolated images; and

pseudo-eigenimaging means for providing pseudo-eigenimages corresponding to the orthonormalized images for a finer resolution,

wherein the pseudo-eigenimages are formed with a projection equation responsive to the coarse eigenimages by adding a scaling and a shift to image intensity.

10. A system as defined in claim 9 wherein said orthonormalizing means comprises decomposition means for performing a singular value decomposition.

11. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for brightness and contrast normalization in appearance-based object detection, the method steps comprising:

extracting a plurality of training images;

finding eigenimages corresponding to the training images;

receiving an input image;

forming a projection equation responsive to the eigenimages by adding a scaling and a shift to image intensity and simultaneously solving for intensity normalization parameters;

computing projected and normalized images;

computing an error-of-fit of the projected and normalized images;

thresholding the error-of-fit; and

determining object positions in accordance with the thresholded error-of-fit,

wherein the program step of finding eigenimages comprises:

sub-sampling the training images;

forming training images of coarse resolution in accordance with the sub-sampled images;

computing eigenimages corresponding to the training images of coarse resolution;

interpolating the eigenimages for coarse resolution;

performing orthonormalization on the interpolated images by singular value decomposition; and

providing pseudo-eigenimages corresponding to the orthonormalized images for a finer resolution.

12. A program storage device as defined in claim 11 wherein at least one of said plurality of training images and said input image comprises a single-photon emission computed tomography image.

13. A program storage device as defined in claim 11 wherein the computed error-of-fit is represented by a score image.

14. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for brightness and contrast normalization in appearance-based object detection, the method steps comprising:

extracting a plurality of training images;

finding eigenimages corresponding to the training images;

receiving an input image;

forming a projection equation responsive to the eigenimages by adding a scaling and a shift to image intensity and simultaneously solving for intensity normalization parameters;

computing projected and normalized images;

computing an error-of-fit of the projected and normalized images;

thresholding the error-of-fit; and

determining object positions in accordance with the thresholded error-of-fit,

further comprising method steps for forming eigenimages for multiresolution, including:

sub-sampling a plurality of training images;

forming training images of coarse resolution in accordance with the sub-sampled images;

computing coarse eigenimages corresponding to the training images of coarse resolution;

interpolating the coarse eigenimages for a finer resolution;

orthonormalizing the interpolated images; and

providing pseudo-eigenimages corresponding to the orthonormalized images for a finer resolution,

wherein the pseudo-eigenimages are formed with a projection equation responsive to the coarse eigenimages by adding a scaling and a shift to image intensity.

15. A program storage device as defined in claim 14 wherein the program step of orthonormalizing the interpolated images comprises performing a singular value decomposition.