Abstract: A semiconductor package is provided, which includes a first chip disposed over a first package substrate, a molding compound surrounding the first chip, a first thermal interface material disposed over the first chip and the molding compound, a heat spreader disposed over the thermal interface material, and a second thermal interface material disposed over the heat spreader. The first thermal interface material and the second thermal interface material have an identical width.

Abstract: A semiconductor structure, comprising a redistribution layer (RDL) including a dielectric layer and a conductive trace within the dielectric layer; a first conductive member disposed over the RDL and electrically connected with the conductive trace; a second conductive member disposed over the RDL and electrically connected with the conductive trace; a first die disposed over the RDL; a second die disposed over the first die, the first conductive member and the second conductive member; and a connector disposed between the second die and the second conductive member to electrically connect the second die with the conductive trace, wherein the first conductive member is electrically isolated from the second die.

Abstract: The invention features a system wherein a recognition environment utilizes comparative advantages of automated feature signature analysis and human perception to form a synergistic data and information processing system for scene structure modeling and testing, object extraction, object linking, and event/activity detection using multi-source sensor data and imagery in both static and time-varying formats. The scene structure and modeling and testing utilizes quantifiable and implementable human language key words. The invention implements real-time terrain categorization and situational awareness plus a dynamic ground control point selection and evaluation system in a Virtual Transverse Mercator (VTM) geogridded Equi-Distance system (ES) environment. The system can be applied to video imagery to define and detect objects/features, events and activity.

Abstract: A system that offers a method of capturing, analyzing, and visualizing a matrix of data for object and feature extraction. This is accomplished by reading a matrix of data represented by a plurality of data types into a processor via a data capture system. The matrix of data is overlaid by a control grid to form a regular matrix having a plurality of cells. A data search spatial radius is created from a point in each cell. Data is then processed from the matrix and certain characteristics are captured and represent each variable in each cell of the matrix, and then output, respectively.

Abstract: A method of recognizing an object in an image is provided using multi-sensor integration through conditionally optimal geo-scene generation and registration. At least two images, one of which is a conditionally optimum, ortho-rectified base image, are input and used to generate a geoscene using ground control points in a latitude-longitude geospatial domain. Georegistration of the geoscene produces a registered geoimage which may be output. A virtual geospatial information system database may be compiled from the georegistered images. A Virtual Transverse Mercator (VTM) projection is defined which allows processing of images falling on both sides of the equator or across traditional UTM boundaries. The georegistration process utilizes the union and the intersection of image pixels, and geooverlaying with interacting layers including geogrids and text layers, to define main body and background pixels to facilitate object recognition.

Abstract: A method of recognizing an object in an image using multi-sensor integration through conditionally optimal geoscene generation and registration is provided. At least two images, one of which is a conditionally optimum, ortho-rectified base image, are input and used to generate a geoscene using at least two ground control points in a latitude-longitude geospatial domain. Georegistration of the geoscene produces a registered geoimage which may be output. A virtual geospatial information system database may be compiled from the georegistered images. A virtual transverse Mercator (VTM) projection is defined which allows processing images falling on both sides of the equator or across traditional UTM boundaries. An Affine transform is used for coordinate transformation in generating geoscenes.

Abstract: The present invention features a method for identifying objects in an image and automatically generating of object recognition code. First, an image is segmented and coded in a first plane in at least one segmentation domain to create a first set of uniform fields or regions having interior and exterior information. Then the image is segmented and coded in a second plane, again in at least one segmentation domain, to create a second set of uniform fields or regions having interior and exterior information. The relationship of the boundaries of the first and second sets of fields is then determined. Information representative of the uniform fields is analyzed and/or communicated horizontally and vertically for relationships of objects among the planes. The system is then queried, forming object definitions, in order to recognize objects in the image. The objects can also be displayed on a common image domain. The image can also be resegmented, each field being coded by a multi-bit (e.g.

Abstract: A method of training a user to identify an object in an image, by querying a computer system having a lexicon of photo-interpreters to formulate object extraction rules. A database to be queried by an expert photo analyst is generated and a programming language is provided to generate extraction rules against that database. Graphical query results are displayed to determine whether an object has been identified. First, a hyperspectral image cube is represented by a set of fraction planes and texture transforms. Mean spectral reading values are obtained and used to build a pseudo multivariate distribution of the values. Recognizable features are then extracted from the hyperspectral image cube. A textural transform of a hyperspectral image cube results. The hundreds of image bands reduced to a few texture transforms can be used to train users of the image recognition system.

Abstract: The present invention relates to an apparatus and a method for object detection in an image. The apparatus for this invention includes a preprocessor, a detector, a segmentor, a classifier, a classifier systems integrator, a system output and a post processor. The method for object detection allows the user to identify an object by using three approaches: (1) a segmentation detector, (2) a pixel-based detector, and (3) a grid-cell and mesotexture based detector. All three of the aforementioned approaches allows the user to use a pseudo-English programming language in the processing system for object detection. This invention allows the user to use an expert's knowledge and convert it to object based content retrieval algorithms. The user can preserve the segmented scenes of the original data and perform a raster-to-vector conversion which preserves the size and shape of the original objects.

Abstract: The invention features a method wherein a recognition environment utilizes pseudo-English as a programming language to extract simple and complex objects with image-and/or map-data as inputs. Based on this human/computer interface in which pseudo-English is a programming language, the object-recognition system has three major logic modules: (1) an input data module; (2) an information-processing module, coupled with the above-noted human computer interface (HCI) module; and (3) an output module that has a feedback mechanism back to the main information-processing and the input-data module. A physical phenomenon (i.e., one that is visible, audible, tactile, etc.) is analyzed by the information-processing module to determine whether it is susceptible to description or articulation. If not, the phenomenon is matched or compared, via the output module, to a known articulatable, physical-phenomenon model and recognizable features are extracted.

Abstract: The invention features a method wherein a recognition environment utilizers pseudo-English as a programming language to extract simple and complex objects with image—and/or map—data as inputs. Based on this human/computer interface in which pseudo-English is a programming language, the object—recognition system has three major logic modules: (1) an input data module; (2) an information—processing module, coupled with the above—noted human computer interface (HCI) module; and (3) an output module that has a feedback mechanism back to the main information—processing and the input—data module. A physical phenomenon (i.e., one that is visible, audible, tactile, etc.) Is analyzed by the information—processing module to determine weather it is susceptible to description or articulation. If not, the phenomenon is matched or compared, via the output module, to a know articulatable, physical-phenomenon model and recognizable features are extracted.

Abstract: The present invention features the use of the fundamental concept of color perception and multi-level resolution to perform scene segmentation and object/feature extraction in the context of self-determining and self-calibration modes. The technique uses only a single image, instead of multiple images as the input to generate segmented images. Moreover, a flexible and arbitrary scheme is incorporated, rather than a fixed scheme of segmentation analysis. The process allows users to perform digital analysis using any appropriate means for object extraction after an image is segmented. First, an image is retrieved. The image is then transformed into at least two distinct bands. Each transformed image is then projected into a color domain or a multi-level resolution setting. A segmented image is then created from all of the transformed images. The segmented image is analyzed to identify objects. Object identification is achieved by matching a segmented region against an image library.

Abstract: The present invention features the use of the fundamental concept of color perception and multi-level resolution to perform scene segmentation and object/feature extraction in the context of self-determining and self-calibration modes. The technique uses only a single image, instead of multiple images as the input to generate segmented images. Moreover, a flexible and arbitrary scheme is incorporated, rather than a fixed scheme of segmentation analysis. The process allows users to perform digital analysis using any appropriate means for object extraction after an image is segmented. First, an image is retrieved. The image is then transformed into at least two distinct bands. Each transformed image is then projected into a color domain or a multi-level resolution setting. A segmented image is then created from all of the transformed images. The segmented image is analyzed to identify objects. Object identification is achieved by matching a segmented region against an image library.

Abstract: The present invention features the use of the fundamental concept of color perception and multi-level resolution to perform scene segmentation and object/feature extraction in the context of self-determining and self-calibration modes. The technique uses only a single image, instead of multiple images as the input to generate segmented images. Moreover, a flexible and arbitrary scheme is incorporated, rather than a fixed scheme of segmentation analysis. The process allows users to perform digital analysis using any appropriate means for object extraction after an image is segmented. First, an image is retrieved. The image is then transformed into at least two distinct bands. Each transformed image is then projected into a color domain or a multi-level resolution setting. A segmented image is then created from all of the transformed images. The segmented image is analyzed to identify objects. Object identification is achieved by matching a segmented region against an image library.

Abstract: The present invention features a method of identifying and/or extracting an object from multiple fused information sources, such as maps and images. The system allows a user to integrate information freely from multiple sources, such as maps, socio-economic data and various types of images. Data is first retrieved and then processed to transform its pixel representation to a region representation. The region representation is then refined by merging mechanisms, such as segmentation. The identified and/or extracted object can then be visualized by the user. Features or objects can then be extracted using the user's expert rules and confidence levels, which confidence levels may be derived by fuzzy logic.

Abstract: A method of digitally redefining an image is disclosed to simplify the storage and processing required to recreate the image. The image is redefined in greatly reduced digital form. The digital information representing commonly bounded image regions is reduced to only a few digits by recoding the image. An image is optically digitized to fingerprint an interior portion of a region and its boundary. At least one point on the boundary has predetermined coordinate values. The region boundary, the interior portion and the point on the boundary are respectively distinguished from one another by at least three optically distinctive tones. The tones may be colors or shades of gray, with each carrying only one or two digits of information. The data is stored in a storage device for subsequent retrieval or analysis.

Abstract: A system for texture-based automatic detection of man-made objects or targets or features of scenes (automatic target recognition, ATR or detection, ATD) in representations of sensed natural environmental scenes spatially partitions digitized picture elements (pixels) of the scene into plural spatially coordinated groups of pixels and simultaneously determines texture measures including a composite texture measure for each group of pixels. Following self-calibration of the spatially coordinated composite texture measure values along spatially delineated row and orthogonal column directions of groups of pixels, areas of interest (AOIs) are identified as the groups of pixels most likely to contain a man-made object, target or feature in a decision logic which performs a group of statistical tests.

Abstract: The present invention features a method of characterizing texture of an image. The image is interrogated at least twice in accordance with at least two respective spatial threshold rules. A value for each of the interrogations is obtained. A mesotexture index is calculated by dividing the product of the values by the difference thereof. A plurality of resulting mesotexture indices can be used to generate a characteristic curve that uniquely identifies the image. Since the process is not iterative, a plurality of interrogating steps can be performed in parallel.