40 results about "Content based retrieval" patented technology

This invention relates to computer-aided diagnostics using content-based retrieval of histopathological image features. Specifically, the invention relates to the extraction of image features from a histopathological image based on predetermined criteria and their analysis for malignancy determination.

A Mixed Media Reality (MMR) system and associated techniques are disclosed. The MMR system provides mechanisms for forming a mixed media document that includes media of at least two types (e.g., printed paper as a first medium and digital content and/or web link as a second medium). In one particular embodiment, the MMR system includes a content-based retrieval database configured with an index table to represent two-dimensional geometric relationships between objects extracted from a printed document in a way that allows look-up using a text-based index. A ranked set of document, page and location hypotheses can be computed given data from the index table. The techniques effectively transform features detected in an image patch into textual terms (or other searchable features) that represent both the features themselves and the geometric relationship between them. A storage facility can be used to store additional characteristics about each document image patch.

A method for selecting a subject for a clinical study includes providing a criteria for selecting one or more subjects from a database, performing a content based similarity search of the database to retrieve subjects who meet the selection criteria, presenting the selected subjects to a user, and receiving user feedback regarding the selected subjects. The feedback can concern whether each of the selected subjects presented to the user is suitable for the clinical study. The method also includes learning from the feedback to improve the content based similarity search, performing an improved content based similarity search of the database to retrieve additional subjects who meet the selection criteria, and presenting the additional subjects to the user.

A scale-Space feature extraction technique is based on recursive decomposition of polyhedral surfaces into surface patches. The experimental results show that this technique can be used to perform matching based on local model structure. Scale-space techniques can be parameterized to generate decompositions that correspond to manufacturing, assembly or surface features relevant to mechanical design. One application of these techniques is to support matching and content-based retrieval of solid models. Scale-space technique can extract features that are invariant with respect to the global structure of the model as well as small perturbations that 3D laser scanning may introduce. A new distance function defined on triangles instead of points is introduced. This technique offers a new way to control the feature decomposition process, which results in extraction of features that are more meaningful from an engineering viewpoint. The technique is computationally practical for use in indexing large models.

For digital pathology imaging, intelligent processing, such as automatic recognition or content-based retrieval, is one significant benefit that drives the wide application of this technology. Before any intelligent processing on pathology images, every image is converted into a feature vector which quantitatively capture its visual characteristics. An algorithm characterizing pathology images with statistical analysis of local responses of neural networks is described herein. The algorithm framework enables extracting sophisticated textural features that are well adapted to the image data of interest.

A search system (200) for a database (224) including records having a multiple disparate types of media is provided. The search system supports queries, that include different types of search criteria, including content based retrieval search criteria. A fuzzy logic method (400) is provided for effectively combining the results of different types of search criteria. The fuzzy logic method also allows confidence levels entered by the user for search criteria to be considered in combining results. Retrieval relevance values for documents for at least some search criteria are used in the fuzzy logic method. For content based image retrieval searches, the retrieval relevance values are computed by mapping a distance between quantitative characterizations of a search basis image, and other images into a finite range.

An audio analysis system for contents including: an audio flow obtaining module, an audio flow segment module, an audio flow type judgment module, a phone flow analysis module and a key word search module based on spelling sequences, in which, the audio flow obtaining module gets an audio flow from outside and sends it to the segment module to segment it to enable each section has a single acoustic character, and the audio flow with a single character is sent to the audio flow judgment module for analysis to get its character kind, the segment determined to be non-phonetic is cast away and the phone audio segments are sent to the phone analysis module to get a spelling pattern and then the key word search module based on the spelling sequence searches the key words to get the position in the audio flow.

The invention discloses a content-based retrieval method and a content-based retrieval system facing radiographs in a PACS database. The content-based retrieval to the radiographs is realized by associating a radiodiagnosis report in a radio information system with the radiographs in the PACS database, establishing the reverse index of the radiodiagnosis report and a feature index library of the radiographs, and then using a two-phase search algorithm. The retrieval method, by effectively integrating text retrieval technology and content-based image retrieval technology, overcomes the defect that the prior content-based image retrieval technology is not suitable for large-scale image databases, alleviates the semantic gap in the prior content-based image retrieval technology to a certain extent, and has high application value.

A method and system for video-content based retrieval is described. A query video depicting an activity is processed using interest point selection to find locations in the video that are relevant to that activity. A set of spatio-temporal descriptors such as self-similarity and 3-D SIFT are calculated within a local neighborhood of the set of interest points. An indexed video database containing videos similar to the query video is searched using the set of descriptors to obtain a set of candidate videos. The videos in the video database are indexed hierarchically using a vocabulary tree or other hierarchical indexing mechanism.

The invention discloses a CAD semantic model search method based on a design intent. The method comprises the steps of A, establishing a three-dimensional CAD model database and carrying out three-dimensional annotation of the design intent through utilization of a PMI module of UG according to modeling, analyzing and manufacturing features of each model; B, carrying out classification on the annotation information of three-dimensional models according to modeling information, analyzing information and manufacturing information, and establishing a design intent semantic tree of each model; C, establishing a field-based body semantic model tree according to a three-dimensional semantic tree database; D, establishing a search index according to the body semantic tree; E, comparing similarity of a target search word set and semantic tree nodes and returning the same or similar nodes and sub-nodes thereof; and F, calculating corresponding model semantic similarity according to the returned nodes, returning the three-dimensional models with high semantic similarity and feeding back the three-dimensional models to a user. According to the method, the semantic gap problem of the content-based search method is solved, the similarity calculation is carried out by matching target search words and semantic annotation words, and the recall ratio of search is improved.

The invention relates to a characteristic reduction-based face detection method in the technical field of pattern recognition. The face detection method comprises the following steps: step 1. reducing Haar-like characteristics, calculating tonal value of each Haar-like characteristic through an integrogram for positive and negative samples, then acquiring peak values of accumulative tonal value histograms for the positive and negative samples, judging recognition capability of the characteristic for a face or a non-face according to relative positions of the peak values of the accumulative tonal value histograms for the positive and negative samples, and determining whether the characteristics is removed or retained; step 2 training the reduced Haar-like characteristics and selecting an optimal weak classifier meeting conditions; and step 3 detecting a face picture by the optimal weak classifier obtained by training. The method ensures the accuracy of face detection, simultaneously solves the problem of time consumption lying in an AdaBoost method. In addition, the method is also applied in the fields of security access control, video monitoring, content-based retrieval, new generation of man-machine interface, and the like.

The invention discloses a method and a system for building an image database. The method comprises the following steps of utilizing keywords to automatically download images from the Internet, carrying out object detection on the downloaded images, carrying out preliminary filtering, carrying out fine contour segmentation on detected objects to obtain segmentation pixels, and filtering the obtained segmentation pixels based on contour match to form the image database. The database can generally achieve 80-90 percent of tagging accuracy, and a user can quickly carry out content-based retrieval on the image database in modes such as draft drawing or framework adjustment so as to quickly find the needed image synthesis and creating resources.

The invention relates to a method for constructing the index for content-based heavy-capacity picture fast search, belonging to an intelligent information processing technique. In the existing techniques, the searching efficiency is low and the system robustness is not strong enough. For this, on the basis of balancing the index structure of multipath search trees, the invention introduces a clustering regulation mechanism and advances a minimum complete subtree updating policy and a nonlinear property quantization algorithm. The invention will largely enhance the performance of the index structure, reduces search response time and enhances the system robustness, and has an important application value in the content-based heavy-capacity picture fast searching system.

The invention relates to a block chain data processing method supporting relational retrieval. The method comprises the steps of obtaining transaction data and block head data in block chain data; storing the transaction data into a preset transaction table of a first preset database, the first preset database being a block chain underlying database, and the preset transaction table being providedwith a block number field; storing the block header data in a preset block table of the first preset database, wherein the preset block table is provided with a block number field; and establishing amapping relationship between the transaction data and the block header data based on the block number field. By implementing the method and the device, the block chain data can support fine-grained content-based retrieval of a transaction level, and meanwhile, the block chain data can support SQL (Structured Query Language), and complicated query operation can be carried out.

The invention discloses a method of achieving intelligent digital tour guide in a museum and relates to the field of digital multi-media. The method of achieving the intelligent digital tour guide in the museum comprises building a high-dimension image data base and a low-resolution image data base which is used for positioning; storing the high-dimension image data base and the low-resolution image data base on a server and aligning the images of the high-dimension image data base and the low-resolution image data base by utilizing a normalized coordinate; organizing the high-dimension image in a pyramid type with multi-resolution and storing every pyramid layer which is separated into image blocks on the server; taking pictures through a camera of a mobile platform and transmitting to the server; positioning through the server and reporting back position information to the mobile platform; enabling the mobile platform to send the position information and reducing degree which are performed as parameters to the server; enabling the server to find a corresponding pyramid layer according to enlarging and reducing degree value and transmit a corresponding image block to the mobile platform; and enabling the mobile platform to display. The server achieves positioning by utilizing SIFT (Scale Invariant Feature Transform). The method of achieving the intelligent digital tour guide in the museum achieves the positioning of the attention areas of users by taking pictures and through searching algorithm and blends high-dimension digital image as display content.

Systems and methods for receiving and indexing native digital data and generating signature vectors for subsequent storage and searching for such native digital data in a database of digital data are disclosed. Native digital data may be transformed into associated transform data sets. Such transformation may comprise entropy-like transforms and/or spatial frequency transforms. The native and associated transform data sets may then be partitioned in to spectral components and those spectral components may have statistical moments applied to them to create a signature vector. Other systems and methods for processing non-image digital data are disclosed. Non-image digital data may be transformed into an amplitude vs time data set and a spectrogram may then be applied to such data sets. Such transformed data sets may then be processed as described.

The invention relates to a k nearby high-dimension inquire method based on data grid. Wherein, the invention via vector reduction, package transmission and product line reduces the response time of k nearby inquire. The execute node of distance calculation is dynamically set by the node condition of mesh, with better expandable property. And since the search based on content is high-dimension search, the invention can be transplanted to the searches of variable mediums.

Disclosed is an apparatus and a method for providing a content-based retrieval function using a mobile communication terminal, the apparatus including a transmitter/receiver for communicating with a data server capable of content-based retrieval and a controller for controlling a transmission of a query to the data server via the transmitter/receiver in a multimedia transmission scheme and a reception of a query result from the data server via the transmitter/receiver.

The invention provides a video semantic gateway. By analyzing and understanding the lower-layer information of video contents, the information of three layers of semantics, namely feeling semantics, structural semantics and conceptual semantics is acquired, researched in a layered mode and gradually perfected, and a video retrieval model based on the three layers of semantics is constructed and realized on a video gateway. With the video semantic gateway, content-based retrieval on a network and in a video library can be realized, and a retrieval interface based on content semantics is nor required to be provided by a resource provider. By the video semantic gateway, the reliability of video analysis and the speed and the efficiency of video retrieval can be improved.

Content-based retrieval of digital pathology images (DPI) is a fundamental component in an intelligent DPI processing and management system. One key issue of content-based DPI retrieval is how to represent an image as a feature vector, capturing its key information that is most relevant to the goal of retrieval. A unified framework of extracting information of different levels for DPI, namely low level color information, middle level texture information and high level diagnostic information is described herein. Such information from all the levels are integrated to the end of content-based DPI retrieval.