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: Systems and approaches for searching a content collection corresponding to query content are provided. In particular, false positive match rates between the query content and the content collection may be reduced with a minimum content region test and/or a minimum features per scale test. For example, by correlating content descriptors of a content piece in the content collection with query descriptors of the query content, the content piece can be determined to match the query content when a particular region of the content piece and/or a particular region of a query descriptor have a proportionate size meeting or exceeding a specified minimum. Alternatively, or in addition, the false positive match rate between query content and a content piece can be reduced by comparing content descriptors and query descriptors of features at a plurality of scales. A content piece can be determined to match the query content according to descriptor proportion quotas for the plurality of scales.

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: Multiple paths of an index tree may be traversed to discover a set of content descriptors that are match candidates for a set of query descriptors. A size of the set of candidate content descriptors may be optimized, for example, to reduce false positive matching errors, query latencies and/or index tree traversal times, at least in part by determining a number of child nodes to traverse based at least in part on current traverse level and/or traverse neighborhood thresholds. Index trees for large content descriptor sets may be built in resource constrained environments with approximation and/or refining build techniques.

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 system, method, and computer program determines section information of a digital volume. Digital volumes include digital representations of human-readable content, such as digitized books. Phrases are extracted from a table of contents of a digital volume. Matching phrases that at least approximately match the extracted phrases are identified in the body of the digital volume. A best matching phrase is determined for each extracted phrase based on the ordering of the extracted phrases and the matching phrases, and based on match scores indicating the quality of the matches. Section information is generated, including section headings and section start locations based on the best matching phrases. The digital volume is presented to users with links from the table of contents to the section headings on the section start pages. The section information is also used to enhance searching of the digital volume by users.

Abstract: Systems and approaches for searching a content collection corresponding to query content are provided. In particular, false positive match rates between the query content and the content collection may be reduced with a minimum content region test and/or a minimum features per scale test. For example, by correlating content descriptors of a content piece in the content collection with query descriptors of the query content, the content piece can be determined to match the query content when a particular region of the content piece and/or a particular region of a query descriptor have a proportionate size meeting or exceeding a specified minimum. Alternatively, or in addition, the false positive match rate between query content and a content piece can be reduced by comparing content descriptors and query descriptors of features at a plurality of scales. A content piece can be determined to match the query content according to descriptor proportion quotas for the plurality of scales.

Abstract: A system identifies metadata associated with a document by capturing text of a document and comparing the text of the document with a collection of metadata records. Sets of matches between the text of the document and at least one record in the collection of metadata records may be identified, where each set of matches corresponds to a metadata record in the collection of metadata records. Metadata records corresponding to each set of matches may be scored. At least one of the metadata records may be identified based on the scores of the metadata records. The at least one identified metadata record may be associated with the document.

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: Multiple paths of an index tree may be traversed to discover a set of content descriptors that are match candidates for a set of query descriptors. A size of the set of candidate content descriptors may be optimized, for example, to reduce false positive matching errors, query latencies and/or index tree traversal times, at least in part by determining a number of child nodes to traverse based at least in part on current traverse level and/or traverse neighborhood thresholds. Index trees for large content descriptor sets may be built in resource constrained environments with approximation and/or refining build techniques.

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: False positive match rates between query content and content in a collection may be reduced with a minimum content region test and/or a minimum features per scale test. The quality of correlations between query descriptors and content descriptors may be improved with a modified sub-region descriptor construction. Content regions associated with detected content features may be partitioned into disjoint sets of sub-regions that cover the content regions, the sub-regions modified so as to at least partially overlap, and descriptor components generated for the modified sub-regions. Matching of feature-sparse content may be improved by adding blurred versions to the collection.

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: Systems and methods for character-by-character alignment of two character sequences (such as OCR output from a scanned document and an electronic version of the same document) using a Hidden Markov Model (HMM) in a hierarchical fashion are disclosed. The method may include aligning two character sequences utilizing multiple hierarchical levels. For each hierarchical level above a final hierarchical level, the aligning may include parsing character subsequences from the two character sequences, performing an alignment of the character subsequences, and designating aligned character subsequences as the anchors, the parsing and performing the alignment being between the anchors generated from an immediately previous hierarchical level if the current hierarchical level is below the first hierarchical level. For the final hierarchical level, the aligning includes performing a character-by-character alignment of characters between anchors generated from the immediately previous hierarchical level.

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: Image-based searching for information on a network is provided in response to an image query sent by a user. The image query includes an image captured using a mobile communications device with a camera. The image is processed to detect any text present in the image, and any detected text can be analyzed using a process such as optical character recognition (OCR). The analyzed text is used to search for matches in at least one corresponding domain database, selected from various domain databases present in the network. Thereafter, one or more selected matches and any additional related information can be sent to the user as one or more results for the submitted image query.

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 lo 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: An image retrieval method which includes producing multiscale vectors associated with points in a set of database images, indexing the database vectors to produce a database vector index, producing query multiscale vectors associated with points in a query image, and matching the query vectors with the indexed database vectors to identify a database image which is similar to the query image. Each of the database multiscale vectors and the query multiscale vectors includes multiple single scale vectors associated with corresponding spatial scales. The method can include applying a single scale image processing procedure at each of the spatial scales to produce single scale vectors and combining single scale vectors each associate with a given point in an image to form a multiscale vector associated with that point.