156 results about "Image query" patented technology

An MMR system includes an analytics module for monitoring and analyzing the creation and usage of visual content search. The analytics module is part of a MMR gateway and provides a mechanism for administrators to determine the usage patterns and other information about users of the MMR system. This information is fed back to other components of the MMR system to improve its operation. The analytics module comprises a monitoring module, a usage database, an access analysis module and a presentation module. The monitoring module is coupled to other components of the MMR gateway and collects information about retrieval request, image queries, context information and recognition results. The usage database stores the information collected by the monitoring module. The access analysis module performs queries on the usage database and analyzes the results. The output of the access analysis module is provided to the presentation module for presentation or output to other systems and users.

An image management method and system provides for storing, indexing, searching and/or retrieving image data. The content of an image collection is pre-processed to identify stable and repeatable keypoints for each image in the collection. Fingerprint information is computed from local groups of keypoints, and the resulting fingerprint information is stored in a compact fingerprint database. The computing of the fingerprint information is based on combinations of a subgroup of the strongest keypoints in an image, called anchor keypoints, in addition to a number of non-anchor keypoints. For each fingerprint in the compact fingerprint database, a sequence of candidate fingerprint combinations is generated and stored in a Fan Tree and/or hashtable and a corresponding fingerprint data structure. The sequence of fingerprint combinations allows several non-anchor keypoints to be missing, while still allowing the system and method to correctly detect fingerprints with high accuracy. A realtime image query is performed by identifying keypoints and computing fingerprints from the query image and matching the query fingerprints to the existing Fan Tree and/or hashtable fingerprint data to determine the best matching image or set of images within the collection. At least one target image is retrieved based on the determining operation, and the retrieved target image is displayed, printed, stored and/or transmitted.

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.

An image query system, and associated method and computer program product are disclosed that enhance and accelerate image-based querying. To this end, the present invention presents a digital image query with implict and explicit associated metadata and retrieval of visually similar images or other pertinent information from a large collection of images stored on local, networked, or web-linked repositories.

An MMR system for publishing comprises a plurality of mobile devices, an MMR gateway, an MMR matching unit and an MMR publisher integrated into a network with an advertiser, an ad broker, and an MMR service bureau. The MMR matching unit receives an image query from the MMR gateway and sends it to one or more of the recognition units to identify a result including a document, the page and the location on the page. The MMR service bureau uses the result to retrieve advertising or other links associated with the location on the page. The list of results and links are sent back to the MMR gateway for presentation on the mobile device. The present invention also includes a number of novel methods including a differentially weighting links associated with an MMR document.

A MMR system for newspaper publishing comprises a plurality of mobile devices, an MMR gateway, an MMR matching unit and an MMR publisher. The MMR matching unit receives an image query from the MMR gateway and sends it to one or more of the recognition units to identify a result including a document, the page and the location on the page. The MMR system also includes a quality predictor as a plug-in installed on the mobile device to filter images before they are included as part of a retrieval request or as part of the MMR matching unit. The quality predictor comprises an input for receiving recognition algorithm information, a vector calculator, a score generator and a scoring module. The quality predictor receives as inputs an image query, context information and device parameters, and generates an outputs a recognizability score. The present invention also includes a method for generating robustness features.

A MMR system for newspaper publishing comprises a plurality of mobile devices, an MMR gateway, an MMR matching unit and an MMR publisher. The MMR matching unit receives an image query from the MMR gateway and sends it to one or more of the recognition units to identify a result including a document, the page and the location on the page. The image registration unit includes an indexing unit for generating images adapted to the environment and capabilities of the image capture device. The indexing unit also automatically adapts the configuration of the plurality of recognition units and index tables based upon image queries applied to the plurality of recognition and index tables. The plurality of recognition units and index tables are configured based on content they reference, recognition algorithm used or other factors. The present invention also includes a number of novel methods including a method for generating blurry images for device training; a method for generating classifiers; a method for selecting a pass classifier; and a method for modifying a hypothesizing and testing classifier on unrecognized images.

A MMR system for publishing comprises a plurality of mobile devices, an MMR gateway, an MMR matching unit and an MMR publisher. The mobile devices send retrieval requests including image queries and other contextual information. The MMR gateway processes the retrieval request from the mobile devices and then generates an image query that is passed on to the MMR matching unit. The MMR matching unit receives an image query from the MMR gateway and sends it to one or more of the recognition units to identify a result including a document, the page and the location on the page. The MMR matching unit includes an image registration unit that receives new content from the MMR publisher and updates the index table of the MMR matching unit. A method for automatically registering images and other data with the MMR matching unit, a method for dynamic load balancing and a method for image-feature-based queue ordering are also included.

The present invention discloses an object-based image search system and method, whereby a user may visually specify query objects for retrieving relevant images without using any image-segmenting software tool. The method of the present invention comprises: specifying target feature points from sample images which are displayed in an image query interface and determining logic relationships of the target feature points; utilizing a feature-point checking program to correlate the target feature points with target objects; utilizing a feature-similarity calculating program to find out the images relevant to the target objects via the image feature parameters stored in a feature database; arranging and presenting the relevant images in sequence.

A system and method for comparing a text image with or without a wildcard character and a character string are provided. The method includes embedding a character string into a vectorial space by extracting a set of features from the character string and generating a character string representation based on the extracted features, such as a spatial pyramid bag of characters (SPBOC) representation. A text image is embedded into a vectorial space by extracting a set of features from the text image and generating a text image representation based on the text image extracted features. A similarity between the text image representation and the character string representation is computed, which includes computing a function of the text image representation and character string representation.

The invention particularly relates to a multi-semantic deep supervision cross-mode hash retrieval method. According to the multi-semantic deep supervision cross-mode hash retrieval method, the methodcomprises the following steps: utilizing a deep neural network, combining supervision semantic information of training data, and learning hash mapping models of multiple modes respectively; sending image query data of a given specific mode into a neural network of a corresponding mode, converting the image mode data into a hash code through hash mapping learned by a deep network, then calculatingthe distance between the hash code and a hash code of another mode in a database, and finally returning data most similar to query. According to the multi-semantic deep supervision cross-mode hash retrieval method, various high-level semantic information is fully utilized, the similarity relation between data modes and label semantic information in the modes are kept, high-quality hash codes can be obtained, hash learning and classification tasks are combined in the same stream for learning, the learning efficiency is improved, and then information retrieval between data of different modes isachieved.

A MMR system for newspaper publishing comprises a plurality of mobile devices, an MMR gateway, an MMR matching unit and an MMR publisher. The MMR matching unit receives an image query from the MMR gateway and sends it to one or more of the recognition units to identify a result including a document, the page and the location on the page. The MMR matching unit also includes a result combiner coupled to each of the recognition units to receive recognition results. The result combiner produces a list of most likely results and associated confidence scores. This list of results is sent by the result combiner back to the MMR gateway for presentation on the mobile device. The result combiner uses the quality predictor as an input in deciding which results are best. The present invention also includes a number of novel methods including a method for generating the list of best results.

The invention discloses an image retrieval system and an image retrieval method based on FPGA. According to the image retrieval system, a solid state disk is used as an image database, and an image library generating module and an image query module are achieved in the master control FPGA chip of the image retrieval system. The method comprises the steps of inputting an image to be queried by a user, and after extracting the feature information of the image, sorting images according to the matching degrees through performing similarity comparison between the feature information with presort feature in the image library. The innovation of the image retrieval system and the image retrieval method provided by the invention lies in that the solid state disk is used for achieving the establishment of the image library and the measurement of the image similarity, the computational burden of the CPU is reduced, the retrieval process is accelerated, and the timeliness of retrieving in mass image data is improved.

The invention discloses a latent semantic image retrieval method of region-oriented multi-feature integration and multi-level feedback. It uses result list returned by the initial keyword search, extracting a variety of region-oriented images characteristics, constructing attribute-image matrix, using latent semantic indexing algorithm to get the semantic space of image sets and semantic features of each image, and then using similar images by users feedback to construct or update image query vector, searching again the semantic space, calculating image semantics features and images inquiries vector similarity, getting outcome sets by descending order, and repeatable retrieval. The invention takes full advantage of image content information, making up for the deficiencies of the keyword search, and through the region-oriented multi-feature integration, enhances image content information from the bottom physical layer to the object layer, then further enhances to the semantic layer by HCI feedback, thereby reducing the gap between the image bottom features and high-level semantic, and allowing Web image retrieval to get higher retrieval accuracy.

The invention discloses an image classification method and system based on small sample learning, a storage medium and a terminal. The method comprises the steps of determining a to-be-classified image data set; extracting a plurality of types of image data samples in the image data set, and establishing an image support set based on the plurality of types of image data samples; extracting a plurality of types of second image data samples from the remaining image data samples after extraction in the image data set to construct a query set; and performing generalization processing on a pre-trained small sample classification network according to the image support set, inputting each image data sample in the image query set into the generalized small sample classification network, and outputting the category of each image data sample. Therefore, by adopting the embodiment of the invention, the feature fusion processing is carried out by extracting the sample features of the support set and the query set, so that the two sets mutually enhance the related features between the samples to highlight the features interested between the samples, and the image classification precision is improved.