Method and system for matching an image using normalized feature vectors
First Claim
1. A computer-implemented method for matching a query image, comprising:
- obtaining a request to match at least one portion of the query image to at least one respective portion of one or more of a plurality of database images;
identifying a plurality of features for at least one Gaussian pyramid image generated for the query image;
for each feature,determining a patch encompassing the feature based at least in part upon one or more orientations for the feature and a sampling factor of the at least one Gaussian pyramid image;
determining components of a feature vector corresponding to a mini-patch obtained from dividing the patch, wherein the components comprise one or more of;
a sum of all positive x-derivatives of the at least one Gaussian pyramid image present in the mini-patch;
a negative of a sum of all negative x-derivatives of the at least one Gaussian pyramid image present in the mini-patch;
a sum of all positive y-derivatives of the at least one Gaussian pyramid image present in the mini-patch; and
a negative of a sum of all negative y-derivatives of the at least one Gaussian pyramid image present in the mini-patch;
normalizing the feature vector for the patch;
determining at least one matching image from among the plurality of database images based at least in part upon comparing feature vectors of each database image to one or more normalized feature vectors of the query image, each of the plurality of features corresponding to one of the normalized feature vectors; and
providing information relating to the at least one matching image in response to the request.
0 Assignments
0 Petitions
Accused Products
Abstract
A method, system and computer program product for encoding an image is provided. The image that needs to be represented is represented in the form of a Gaussian pyramid which is a scale-space representation of the image and includes several pyramid images. The feature points in the pyramid images are identified and a specified number of feature points are selected. The orientations of the selected feature points are obtained by using a set of orientation calculating algorithms. A patch is extracted around the feature point in the pyramid images based on the orientations of the feature point and the sampling factor of the pyramid image. The boundary patches in the pyramid images are extracted by padding the pyramid images with extra pixels. The feature vectors of the extracted patches are defined. These feature vectors are normalized so that the components in the feature vectors are less than a threshold.
-
Citations
16 Claims
-
1. A computer-implemented method for matching a query image, comprising:
-
obtaining a request to match at least one portion of the query image to at least one respective portion of one or more of a plurality of database images; identifying a plurality of features for at least one Gaussian pyramid image generated for the query image; for each feature, determining a patch encompassing the feature based at least in part upon one or more orientations for the feature and a sampling factor of the at least one Gaussian pyramid image; determining components of a feature vector corresponding to a mini-patch obtained from dividing the patch, wherein the components comprise one or more of; a sum of all positive x-derivatives of the at least one Gaussian pyramid image present in the mini-patch; a negative of a sum of all negative x-derivatives of the at least one Gaussian pyramid image present in the mini-patch; a sum of all positive y-derivatives of the at least one Gaussian pyramid image present in the mini-patch; and a negative of a sum of all negative y-derivatives of the at least one Gaussian pyramid image present in the mini-patch; normalizing the feature vector for the patch; determining at least one matching image from among the plurality of database images based at least in part upon comparing feature vectors of each database image to one or more normalized feature vectors of the query image, each of the plurality of features corresponding to one of the normalized feature vectors; and providing information relating to the at least one matching image in response to the request. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
-
-
9. A system for matching a query image, comprising:
-
at least one processor; and memory including instructions that, upon being executed by the at least one processor, cause the system to; obtain a request to match at least one portion of the query image to at least one respective portion of one or more of a plurality of database images; identify a plurality of features for at least one scaled image generated for the query image; for each feature, determine a patch encompassing the feature based at least in part upon one or more orientations for the feature and a sampling factor of the at least one scaled image; determining components of a feature vector corresponding to a mini-patch obtained from dividing the patch, wherein the components comprise one or more of; a sum of all positive x-derivatives of the at least one Gaussian pyramid image present in the mini-patch; a negative of a sum of all negative x-derivatives of the at least one Gaussian pyramid image present in the mini-patch; a sum of all positive y-derivatives of the at least one Gaussian pyramid image present in the mini-patch; and a negative of a sum of all negative y-derivatives of the at least one Gaussian pyramid image present in the mini-patch; normalize the feature vector for the patch; determine at least one matching image from among the plurality of database images based at least in part upon comparing feature vectors of each database image to one or more normalized feature vectors of the query image, each of the plurality of features corresponding to one of the normalized feature vectors; and provide information relating to the at least one matching image in response to the request. - View Dependent Claims (10)
-
-
11. A non-transitory computer-readable storage medium matching a query image including instructions that, upon being executed by at least one processor of a computing device, cause the computing device to:
-
obtain a request to match at least one portion of the query image to at least one respective portion of one or more of a plurality of database images; identify a plurality of features for the at least one scaled image generated for the query image; for each feature, determine a patch encompassing the feature based at least in part upon one or more orientations for the feature and a sampling factor of the at least one scaled image; determining components of a feature vector corresponding to a mini-patch obtained from dividing the patch, wherein the components comprise one or more of; a sum of all positive x-derivatives of the at least one Gaussian pyramid image present in the mini-patch; a negative of a sum of all negative x-derivatives of the at least one Gaussian pyramid image present in the mini-patch; a sum of all positive y-derivatives of the at least one Gaussian pyramid image present in the mini-patch; and a negative of a sum of all negative y-derivatives of the at least one Gaussian pyramid image present in the mini-patch; normalize the feature vector for the patch; determine at least one matching image from among the plurality of database images based at least in part upon comparing feature vectors of each database image to one or more normalized feature vectors of the query image, each of the plurality of features corresponding to one of the normalized feature vectors; and provide information relating to the at least one matching image in response to the request. - View Dependent Claims (12, 13, 14, 15, 16)
-
Specification