Abstract: Advantages of both conventional and digital maps can be obtained by utilizing a physical map as a type of input to any of various processing devices. In various embodiments, a user can capture an image of a physical map that includes at least one location of interest. The captured image can be matched with stored map information to obtain location information corresponding to the captured image. The location information can be used to provide any of a variety of types of functionality to the user, such as providing navigation directions to that location, displaying information about attractions around that location or statistics about that location, etc. The user in some embodiments can annotate the map to provide additional input, such as areas of interest, exclusion regions, and/or proposed driving routes.

Abstract: Advantages of both conventional and digital maps can be obtained by utilizing a physical map as a type of input to any of various processing devices. In various embodiments, a user can capture an image of a physical map that includes at least one location of interest. The captured image can be matched with stored map information to obtain location information corresponding to the captured image. The location information can be used to provide any of a variety of types of functionality to the user, such as providing navigation directions to that location, displaying information about attractions around that location or statistics about that location, etc. The user in some embodiments can annotate the map to provide additional input, such as areas of interest, exclusion regions, and/or proposed driving routes.

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.

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.

Abstract: A method, system and computer program product for virtually placing an object on an image of a human appendage is provided. First, image boundaries are detected in the image of the appendage and converted into a set of line segments. A pair of line segments is evaluated according to a function that combines subscores of the pair of line segments to produce a score. The subscores of the line segments are computed based on various properties such as orientation difference, extent, proximity to the center of the image, bilateral symmetry, and the number of skin-colored pixels. A pair of line segments with the highest score is chosen as the appendage boundaries and is used to determine the position, orientation, and extent of the object. The image of the object is then transformed according to the determined parameters and combined with the image of the appendage to produce the desired result.

Abstract: Various embodiments of the present invention relate to a method, system and computer program product for detecting and recognizing text in the images captured by cameras and scanners. First, a series of image-processing techniques is applied to detect text regions in the image. Subsequently, the detected text regions pass through different processing stages that reduce blurring and the negative effects of variable lighting. This results in the creation of multiple images that are versions of the same text region. Some of these multiple versions are sent to a character-recognition system. The resulting texts from each of the versions of the image sent to the character-recognition system are then combined to a single result, wherein the single result is detected text.

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.

Abstract: Present invention relates to a method and system for automatic searching for information on a network in response to an image query sent by a user. The image query includes an image that is captured by using a mobile communications device with a camera. The image is processed to detect the text present in it. The detected text is then recognized using an OCR. Subsequently, the text is searched for matches in the corresponding domain database, selected from the various domain databases present in the network. Thereafter, selected matches and additional related information is sent to the user.

Abstract: A method, system and computer program product for virtually placing an object on an image of a human appendage is provided. First, image boundaries are detected in the image of the appendage and converted into a set of line segments. A pair of line segments is evaluated according to a function that combines subscores of the pair of line segments to produce a score. The subscores of the line segments are computed based on various properties such as orientation difference, extent, proximity to the center of the image, bilateral symmetry, and the number of skin-colored pixels. A pair of line segments with the highest score is chosen as the appendage boundaries and is used to determine the position, orientation, and extent of the object. The image of the object is then transformed according to the determined parameters and combined with the image of the appendage to produce the desired result.

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.

Abstract: Various embodiments of the present invention relate to a method, system and computer program product for detecting and recognizing text in the images captured by cameras and scanners. First, a series of image-processing techniques is applied to detect text regions in the image. Subsequently, the detected text regions pass through different processing stages that reduce blurring and the negative effects of variable lighting. This results in the creation of multiple images that are versions of the same text region. Some of these multiple versions are sent to a character-recognition system. The resulting texts from each of the versions of the image sent to the character-recognition system are then combined to a single result, wherein the single result is detected text.

Abstract: A method, system and computer program product for placing an image of an object on an image of user is provided. First, image boundaries are detected in the image of the user and converted into a set of line segments. A pair of line segments is evaluated according to a function that combines subscores of the pair of line segments to produce a score. The subscores of the line segments are computed based on various properties such as orientation difference, extent, proximity to the center of the image, bilateral symmetry, and the number of skin-colored pixels. A pair of line segments with the highest score is chosen as the boundaries for the image of the user and is used to determine the position, orientation, and extent of the object. The image of the object is then transformed according to the determined parameters and combined with the image of the user to produce the desired result.

Abstract: Various embodiments of the present invention relate to a method, system and computer program product for detecting and recognizing text in the images captured by cameras and scanners. First, a series of image-processing techniques is applied to detect text regions in the image. Subsequently, the detected text regions pass through different processing stages that reduce blurring and the negative effects of variable lighting. This results in the creation of multiple images that are versions of the same text region. Some of these multiple versions are sent to a character-recognition system. The resulting texts from each of the versions of the image sent to the character-recognition system are then combined to a single result, wherein the single result is detected text.

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.

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.

Abstract: Present invention relates to a method and system for automatic searching for information on a network in response to an image query sent by a user. The image query includes an image that is captured by using a mobile communications device with a camera. The image is processed to detect the text present in it. The detected text is then recognized using an OCR. Subsequently, the text is searched for matches in the corresponding domain database, selected from the various domain databases present in the network. Thereafter, selected matches and additional related information is sent to the user.

Abstract: The present invention relates to a method, system, and a computer program product for delivering content to a communication device, in response to an image sent by the communication device. The received image is matched with a plurality of images, and, when a match is found for the received image, content corresponding to the image is delivered to the communication device. The plurality of images is stored in an image database, and the corresponding content is stored in a content repository. The present invention enables a content provider to automatically update the image database and the content repository without any human intervention.

Abstract: A method, system and computer program product for representing 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.

Abstract: A method, system and computer program product for matching images is provided. The images to be matched are represented by feature points and feature vectors and orientations associated with the feature points. First, putative correspondences are determined by using feature vectors. A subset of putative correspondences is selected and the topological equivalence of the subset is determined. The topologically equivalent subset of putative correspondences is used to establish a motion estimation model. An orientation consistency test is performed on the putative correspondences and the corresponding motion estimation transformation that is determined, to avoid an infeasible transformation. A coverage test is performed on the matches that satisfy orientation consistency test. The candidate matches that do not cover a significant portion of one of the images are rejected. The final match images are provided in the order of decreasing matching, in case of multiple images satisfying all the test requirements.

Abstract: A method, system and computer program product for virtually placing an object on an image of a human appendage is provided. First, image boundaries are detected in the image of the appendage and converted into a set of line segments. A pair of line segments is evaluated according to a function that combines subscores of the pair of line segments to produce a score. The subscores of the line segments are computed based on various properties such as orientation difference, extent, proximity to the center of the image, bilateral symmetry, and the number of skin-colored pixels. A pair of line segments with the highest score is chosen as the appendage boundaries and is used to determine the position, orientation, and extent of the object. The image of the object is then transformed according to the determined parameters and combined with the image of the appendage to produce the desired result.