Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points from the template image are then matched to the feature points in the test image. An additional matching technique boosts the number of points that match each other. The additional points improve the match quality and help discriminate true from false positive matches.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points from the template image are then matched to the feature points in the test image. An additional matching technique boosts the number of points that match each other. The additional points improve the match quality and help discriminate true from false positive matches.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points of a template image are determined under various transformations and used to determine a set of composite feature points for each template image. The composite feature points are used to determine if the template image is present in a test image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Classifiers are trained for multiple template images and the classifiers are used to evaluate a match between a template image and a test image.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image, includes: dividing set first image into multiple image regions; for a particular image region of the multiple image regions, determining a particular set of feature points associated with the particular image region; and attempting to match feature points in the particular set of feature points with second feature points associated with the second image to determine whether the particular image region of the first image contains at least a portion of the second image, wherein the first image is considered to contain at least a portion of a second image when the particular image region of the first image contains at least a portion of the second image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points of a template image are determined under various transformations and used to determine a set of composite feature points for each template image. The composite feature points are used to determine if the template image is present in a test image. A covering set for a template image is used to optimize processing of test images.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points of a template image are determined under various transformations and used to determine a set of composite feature points for each template image. The composite feature points are used to determine if the template image is present in a test image.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points of a template image are determined under various transformations and used to determine a set of composite feature points for each template image. The composite feature points are used to determine if the template image is present in a test image. A covering set for a template image is used to optimize processing of test images.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points from the template image are then matched to the feature points in the test image. An additional matching technique boosts the number of points that match each other. The additional points improve the match quality and help discriminate true from false positive matches.

Abstract: An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Classifiers are trained for multiple template images and the classifiers are used to evaluate a match between a template image and a test image.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image, includes: dividing set first image into multiple image regions; for a particular image region of the multiple image regions, determining a particular set of feature points associated with the particular image region; and attempting to match feature points in the particular set of feature points with second feature points associated with the second image to determine whether the particular image region of the first image contains at least a portion of the second image, wherein the first image is considered to contain at least a portion of a second image when the particular image region of the first image contains at least a portion of the second image.

Abstract: A system for preparing and transmitting all desired images from one or more image-producing clients to a server for archiving or later analysis, validation, or reporting purposes. Images are queued on the client while they await transmission to the server and can also be reduced in size, if necessary, to reduce storage space or network transmission time. Once the images reside on the server, they can be added to an image database or used for further processing.

Abstract: A system for taking a sequence of images and converting them to a single composite image that contains the combined visual information of the defects found in the source images. The source images are aligned and manipulated, if necessary, such that they can be superimposed together. Optional image processing steps are applied to further enhance the defects. Both the number of input images and the algorithm used to combine these images can be adjusted to allow an observer to see a persistent display of the defects found in the images. Status, diagnostic and defect information, consisting of graphics and textual messages, are then applied to the composite image for display.

Abstract: A system for taking a sequence of images and converting them to a single composite image that contains the combined visual information of the defects found in the source images. The source images are aligned and manipulated, if necessary, such that they can be superimposed together. Optional image processing steps are applied to further enhance the defects. Both the number of input images and the algorithm used to combine these images can be adjusted to allow an observer to see a persistent display of the defects found in the images. Status, diagnostic and defect information, consisting of graphics and textual messages, are then applied to the composite image for display.

Abstract: A system for preparing and transmitting all desired images from one or more image-producing clients to a server for archiving or later analysis, validation, or reporting purposes. Images are queued on the client while they await transmission to the server and can also be reduced in size, if necessary, to reduce storage space or network transmission time. Once the images reside on the server, they can be added to an image database or used for further processing.