Fast pattern classification based on a sparse transform

A non-transitory computer-readable medium carrying one or more sequences of instructions for determining a feature in a subject image, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform:

• performing a sparse transform on a subject image, wherein the sparse transform is selected from a group comprising a wavelet transform and a Fourier transform, to determine a sparse transformed subject image that represents the subject image with a few significant coefficients compared to a number of values in the subject image at each of a plurality of orientations;
• receiving a plurality of number I of patch functions that each is based on a portion of a sparse transformed image at corresponding orientations for a selected image of a training set of images, wherein the plurality of patch functions represent learned features in the training set;
• and
• determining a feature in the subject image based on the transformed subject image and the plurality of patch functions.

An apparatus for determining a feature in an image, comprising:

• means for performing a sparse transform on a subject image, wherein the sparse transform is selected from a group comprising a wavelet transform and a Fourier transform, to determine a sparse transformed subject image that represents the subject image with a few significant coefficients compared to a number of values in the subject image at each of a plurality of orientations;
• means for-receiving a plurality of number I of patch functions that each is based on a portion of a sparse transformed image at corresponding orientations for a selected image of a training set of images, wherein the plurality of patch functions represent learned features in the training set;
• and
• means for determining a feature in the subject image based on the transformed subject image and the plurality of patch functions.

An apparatus for determining a feature in an image, comprising logic encoded in a tangible medium and configured to:

• perform a sparse transform on a subject image, wherein the sparse transform is selected from a group comprising a wavelet transform and a Fourier transform, to determine a sparse transformed subject image that represents the subject image with a few significant coefficients compared to a number of values in the subject image at each of a plurality of orientations;
• receive a plurality of number I of patch functions that each is based on a portion of a sparse transformed image at corresponding orientations for a selected image of a training set of images, wherein the plurality of patch functions represent learned features in the training set;
• and
• determine a feature in the subject image based on the transformed subject image and the plurality of patch functions.

A method for determining a feature in a subject image, comprising:

• performing a sparse transform on a subject image, wherein the sparse transform is selected from a group comprising a wavelet transform and a Fourier transform, to determine a sparse transformed subject image that represents the subject image with a few significant coefficients compared to a number of values in the subject image at each of one or more orientations;
• receiving a plurality of number I of patch functions that each is based on a random portion of a sparse transformed image at corresponding orientations for a randomly selected image of a training set of images, wherein the plurality of patch functions represent learned features in the training set;
• and
• sending data that indicates a feature in the subject image based on the transformed subject image and the plurality of patch functions.

A non-transitory computer-readable medium carrying one or more sequences of instructions for determining a feature in a subject image, wherein execution of the one or more sequences of instructions by one or more processors causes the one or more processors to perform:

• performing a sparse transform on a subject image, wherein the sparse transform is selected from a group comprising a wavelet transform and a Fourier transform, to determine a sparse transformed subject image that represents the subject image with a few significant coefficients compared to a number of values in the subject image at each of one or more orientations;
• receiving a plurality of number I of patch functions that each is based on a random portion of a sparse transformed image at corresponding orientations for a randomly selected image of a training set of images, wherein the plurality of patch functions represent learned features in the training set;
• and
• determining a feature in the subject image based on the transformed subject image and the plurality of patch functions.

An apparatus for determining a feature in an image, comprising logic encoded in a tangible medium and configured to:

• perform a sparse transform on a subject image, wherein the sparse transform is selected from a group comprising a wavelet transform and a Fourier transform, to determine a sparse transformed subject image that represents the subject image with a few significant coefficients compared to a number of values in the subject image at each of one or more orientations;
• receive a plurality of number I of patch functions that each is based on a random portion of a sparse transformed image at corresponding orientations for a randomly selected image of a training set of images, wherein the plurality of patch functions represent learned features in the training set;
• and
• determine a feature in the subject image based on the transformed subject image and the plurality of patch functions.