Abstract: The invention disclosed herein includes a system and method for electronically transferring data through a communications connection in a transparent manner such that the data transfer does not interfere with other traffic sharing the connection. The invention transfers data using bandwidth of the connection that other traffic are not using. If other traffic desires to use the bandwidth currently being used by the invention, the invention relinquishes the bandwidth to the other traffic and retreats to avoid bandwidth contention. Although a retreat may cause gaps in the data transferred, a key aspect of the invention is that any missing data due to these gaps is recovered easily and in a bandwidth-efficient way using novel error correction and recovery.

Abstract: Apparatus and methods for detecting multiple images in digital image data are described. In one aspect, an edge map is generated from image data. The edge map is analyzed to determine a set of boundaries of the one or more objects by. This analysis is accomplished by: (a) determining a set of transitions between the set of boundaries and a background color; (b) identifying a set of characteristics from the set of transitions, wherein the set of characteristics are used to indicate whether the image data comprises a single object or whether the image data comprises a plurality of objects; and (c) if the image data corresponds to a plurality of objects, assigning particular ones of the set of boundaries to particular ones of the plurality of objects based on a set of rules. The one or more objects are segmented based on the set of boundaries.

Abstract: A background color estimation system and method for estimating a background color of a scanned image. The background color estimation method includes generating a list of candidate background colors present in the image, determining the most common candidate color from the list, and designating the most common candidate background color as the estimated background color. Candidate colors are extracted from the scanned image by examining lines of pixels in the image and generating frequency distributions (such as histograms) of pixel colors within the lines. The frequency value of the most common pixel color in the frequency distribution is compared to a frequency threshold. If the frequency value is greater than the frequency threshold, the most common pixel color is considered a candidate background color. In addition, a variance of the estimated background color is obtained and can be used to intelligently select a threshold for additional image processing techniques.

Abstract: Information about media objects within media streams is inferred based on repeat instances of the media objects within the media streams. A system and methods enable the monitoring of one or more media streams and the identification of repeat instances of media objects (e.g., audio and/or video objects) within the media streams. The monitoring and object repeat identification is performed by one or more server computers on a network. Information about a media object can be inferred based on repeat instances of the media object and based on repeat instances of related media objects. The information is transferred from a server to a client in response to a user query entered at the client through an interactive user interface.

Abstract: Many media streams contain “objects” that repeat. Repeating objects in a media stream are defined as any section of non-negligible duration, i.e., a song, video, advertisement, jingle, etc., which would be considered to be a logical unit by a human listener or viewer. An “object controller” identifies such repeating objects as they occur, and provides an interactive user interface for allowing users to specify how individual repeating objects are to be handled either in real time, or upon subsequent occurrences of particular repeating objects. In general, the object controller includes a mechanism for identifying repeating objects, a mechanism for identifying temporal endpoints of those objects, a user interface for specifying actions to be taken when a particular object repeats within a media stream, and, in one embodiment, a buffer having sufficient length to allow for real-time deletion of objects from the media stream without obvious interruption in the str.

Abstract: An “object extractor” automatically identifies and segments repeating media objects in a media stream. “Objects” are any section of non-negligible duration, i.e., a song, video, advertisement, jingle, etc., which would be considered to be a logical unit by a human listener or viewer. Identification and segmentation of repeating objects is achieved by directly comparing sections of the media stream to identify matching portions of the stream, then aligning the matching portions to identify object endpoints. Alternately, a suite of object dependent algorithms is employed to target particular aspects of the stream for identifying possible objects within the stream. Confirmation of possible objects as repeating objects is achieved by automatically searching for potentially matching objects in a dynamic object database, followed by a detailed comparison to one or more of the potentially matching objects. Object endpoints are then determined by automatic alignment and comparison to other copies of that object.

Abstract: A “composite signal generator” automatically combines two or more copies of a signal to produce a composite that is better than the individual copies. For example, given two or more input images of a scene captured from approximately the same viewpoint, the composite signal generator automatically produces a composite image having reduced or eliminated areas of occlusion with respect to any occlusions existing in the input images. First, the input images are registered using conventional image registration techniques. Differences between the registered images are then used to identify regions of potential occlusion in one or more of the images. A determination of which image is actually occluded is made by identifying which image has a larger discontinuity along a border of the potentially occluded regions. A composite image is then created by choosing one image and mosaicing parts from the other images where it is occluded and they are not.

Abstract: An “interactive signal analyzer” provides a framework for sampling one or more signals, such as, for example, one or more channels across the entire FM radio spectrum in one or more geographic regions, to identify objects of interest within the signal content and associate attributes with that content. The interactive signal analyzer uses a signal fingerprint extraction algorithm, i.e., a “fingerprint engine,” for deriving traces from segments of one or more signals. These traces are referred to as “fingerprints” since they are used to uniquely identify the signal segments from which they are derived. These fingerprints are then used for comparison to a database of fingerprints of known objects of interest. Information describing the identified content and associated object attributes is then provided in an interactive user database for viewing and interacting with information resulting from the comparison of the fingerprints to the database.

Abstract: An “audio challenger” operates by first defining a library of a finite number of discrete audio objects including spoken sounds, such as, for example, individual digits, letters, numbers, words, etc., or combinations of two or more digits, letters, numbers, or words. The spoken sounds are either automatically generated by a computer, or recorded from one or more actual spoken voices. Given this library of audio objects, the audio challenger automatically selects one or more audio objects from the library and concatenates the objects into an audio string that is then automatically processed to add one or more distortions to create a “challenge string.” The distorted challenge string is then presented to an unknown party for identification. If the unknown party correctly identifies the challenge string, then the unknown party is deemed to be a human operator. Otherwise, the unknown party is deemed to be another computer.

Abstract: An object detection and extraction system and method for processing digital image data. The system and method segregates objects contained within a single image and allows those objects to be considered as an individual object. In general, the object detection and extraction method takes an image containing one or more objects of know shape (such as rectangular objects) and finds the number of objects along with their size, orientation and position. In particular, the object detection and extraction method includes classifying each pixel in an image containing one or more objects to obtain pixel classification data, defining an image function to process the pixel classification data, and dividing the image into sub-images based on disparities or gaps in the image function. Each of the sub-images is processed to determine a size and an orientation for the each of the objects. The object detection and extraction system uses the above method.

Abstract: An “object extractor” automatically identifies and segments repeating media objects in a media stream. “Objects” are any section of non-negligible duration, i.e., a song, video, advertisement, jingle, etc., which would be considered to be a logical unit by a human listener or viewer. Identification and segmentation of repeating objects is achieved by directly comparing sections of the media stream to identify matching portions of the stream, then aligning the matching portions to identify object endpoints. Alternately, a suite of object dependent algorithms is employed to target particular aspects of the stream for identifying possible objects within the stream. Confirmation of possible objects as repeating objects is achieved by automatically searching for potentially matching objects in a dynamic object database, followed by a detailed comparison to one or more of the potentially matching objects.

Abstract: A barcode system for generating and decoding a barcode with visual significance. The barcode system of the present invention includes an encoding module for receiving a message and a logo and generating a visually significant barcode based on these inputs. A decoding module is also provided for receiving an acquired version of a visually significant barcode that may have been degraded in a typical document handling channel (e.g., through the printing, scanning, or copying process) and for recovering the message specified by the visually significant barcode.

Abstract: A method and apparatus is described for detection and deterrence of counterfeiting that permits one to make legitimate color copies without introducing visual artifacts or experiencing substantial processing delays. The scheme detects a characteristic color of frequently counterfeited documents and alters the characteristic color in the copies. The scheme exploits the fact that conversion between color spaces is frequently accomplished using a color Look-Up Table (LUT). Because it represents no computational burden to alter the values in the LUT, we can efficiently modulate slightly the value of the characteristic color in a way that depends on the value of the counter. For example, at first even banknote green is rendered correctly. However, as the page uses more and more of the ink, a modulation function causes conversion to a darker value than the actual green requested.

Abstract: A barcode system for generating and decoding a barcode with visual significance. The barcode system of the present invention includes an encoding module for receiving a message and a logo and generating a visually significant barcode based on these inputs. A decoding module is also provided for receiving an acquired version of a visually significant barcode that may have been degraded in a typical document handling channel (e.g., through the printing, scanning, or copying process) and for recovering the message specified by the visually significant barcode.

Abstract: An “object extractor” automatically identifies and segments repeating media objects in a media stream. “Objects” are any section of non-negligible duration, i.e., a song, video, advertisement, jingle, etc., which would be considered to be a logical unit by a human listener or viewer. Identification and segmentation of repeating objects is achieved by directly comparing sections of the media stream to identify matching portions of the stream, then aligning the matching portions to identify object endpoints. Alternately, a suite of object dependent algorithms is employed to target particular aspects of the stream for identifying possible objects within the stream. Confirmation of possible objects as repeating objects is achieved by automatically searching for potentially matching objects in a dynamic object database, followed by a detailed comparison to one or more of the potentially matching objects.

Abstract: Many media streams contain “objects” that repeat. Repeating objects in a media stream are defined as any section of non-negligible duration, i.e., a song, video, advertisement, jingle, etc., which would be considered to be a logical unit by a human listener or viewer. An “object controller” identifies such repeating objects as they occur, and provides an interactive user interface for allowing users to specify how individual repeating objects are to be handled either in real time, or upon subsequent occurrences of particular repeating objects. In general, the object controller includes a mechanism for identifying repeating objects, a mechanism for identifying temporal endpoints of those objects, a user interface for specifying actions to be taken when a particular object repeats within a media stream, and, in one embodiment, a buffer having sufficient length to allow for real-time deletion of objects from the media stream without obvious interruption in the stream.

Abstract: The present invention provides a large capacity, user defined audio content delivery system. The system delivers uninterrupted music and delivers information content (e.g., news by evaluating and encoding an input audio stream while outputting another stream. Undesirable audio content (e.g., advertisements and unwanted news) are not present in the output audio stream as only desired portions of information content are stored for playback on demand. The invention also includes a user interface that is simple enough to facilitate utilization of the audio system in an automobile and employs standard hardware available in typical computing and/or personal digital assistant equipment. Additionally, the audio system can be portable (e.g., as portable as a personal digital assistant) and can be updated in real time or off line via a personal computer.

Abstract: The invention disclosed herein includes a system and method for electronically transferring data through a communications connection in a transparent manner such that the data transfer does not interfere with other traffic sharing the connection. The invention transfers data using bandwidth of the connection that other traffic are not using. If other traffic desires to use the bandwidth currently being used by the invention, the invention relinquishes the bandwidth to the other traffic and retreats to avoid bandwidth contention. Although a retreat may cause gaps in the data transferred, a key aspect of the invention is that any missing data due to these gaps is recovered easily and in a bandwidth-efficient way using novel error correction and recovery.

Abstract: An “object extractor” automatically identifies and segments repeating media objects in a media stream. “Objects” are any section of non-negligible duration, i.e., a song, video, advertisement, jingle, etc., which would be considered to be a logical unit by a human listener or viewer. Identification and segmentation of repeating objects is achieved by directly comparing sections of the media stream to identify matching portions of the stream, then aligning the matching portions to identify object endpoints. Alternately, a suite of object dependent algorithms is employed to target particular aspects of the stream for identifying possible objects within the stream. Confirmation of possible objects as repeating objects is achieved by automatically searching for potentially matching objects in a dynamic object database, followed by a detailed comparison to one or more of the potentially matching objects.

Abstract: Opportunistic image quality improvement in a digital camera. In a digital camera having a picture memory of fixed size for storing a predetermined number of pictures, raw image data is compressed to form primary and auxiliary data sets. The primary data set allows the image to be reconstructed at a first quality level. The primary and auxiliary data sets combined allow the reconstruction of the image at a higher quality level. As images are taken and processed, if sufficient storage space exists in the picture memory, both primary and auxiliary data sets are stored. This continues until the memory is full of primary and auxiliary data sets. Once the memory is full, as more images are taken and stored, the space used by auxiliary data sets is reclaimed for use by primary data sets, and the auxiliary data sets are not stored.