METHOD AND SYSTEM FOR MATCHING AN IMAGE USING NORMALIZED FEATURE VECTORS

摘要

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.

主权项

1. A computer-implemented method, comprising:
obtaining a request to match a query image to at least one of a plurality of database images; generating a Gaussian pyramid image for the query image; analyzing the Gaussian pyramid image to identity a feature represented in the Gaussian pyramid image; determining an orientation of the feature; determining a patch encompassing the feature based at least in part upon the orientation and a sampling factor associated with the Gaussian pyramid image; determining a feature vector for the patch; dividing the patch into a plurality of sub patches; determining components of the feature vector corresponding to a sub patch of the plurality of sub patches; reducing the components associated with a value greater than a threshold to determine a reduced set of components; normalizing components of the reduced set of components associated with respective values less than the threshold to a calculated length to generate a normalized feature vector, the calculated length being based at least in part upon the threshold and a number of components having values exceeding the threshold; and 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 the normalized feature vector.