Abstract: The present disclosure provides methods and systems for processing data. One claim recites a camera-equipped portable computer system, comprising: a camera; one or more processors programed for: i) controlling the camera to capture image data, the captured image data corresponding to the camera's field of view; ii) defining a sub-region comprising image data within the field of view, the sub-region comprising less image data than does the full field of view; and iii) searching image data within the field of view for hidden keys, but limiting a response to detected keys to those only found within the sub-region. Of course other claims and combinations are provided too.

Abstract: A location aware intelligent transportation system determines ranges between a plurality of communication devices, including at least one mobile communication device. A method includes receiving receive messages transmitted from a plurality of other communication devices. Each receive message includes a transmit count stamp corresponding to a remote counter value. The mobile communication device generates a receive count stamp for each receive message. The method includes dynamically associating and disassociating the mobile communication device with a plurality of sub-groups of the plurality of other communication devices. The associating and disassociating are based at least in part on receiving receive messages from a predetermined number of other communication devices for each sub-group.

Abstract: Methods and arrangements involving portable devices, such as smartphones and tablet computers, are disclosed. Exemplary arrangements utilize the camera portions of such devices to identify nearby subjects, and take actions based thereon. Others rely on near field chip (RFID) identification of objects, or on identification of audio streams (e.g., music, voice). Some of the detailed technologies concern improvements to the user interfaces associated with such devices. Others involve use of these devices in connection with shopping, text entry, sign language interpretation, and vision-based discovery. Still other improvements are architectural in nature, e.g., relating to evidence-based state machines, and blackboard systems. Yet other technologies concern use of linked data in portable devices—some of which exploit GPU capabilities. Still other technologies concern computational photography. A great variety of other features and arrangements are also detailed.

Abstract: The location of one or more mobile nodes in a wireless local area network (WLAN) is determined. Nodes in the WLAN include respective ping drivers to generate ping event values related to transmit count stamps and receive count stamps for wireless messages exchanged between the nodes. Each wireless message is associated with a transmit offset corresponding to an expected transmit time. A sorting module groups the ping event values and produces a difference between the respective receive count stamps and the transmit count stamps for each wireless message. Based on the sorted ping event values, the sorting module generates transmit offset values relating to the transmit offsets. A space-time calibration unit generates, from the sorted differences and the transmit offset values, a clock rate solution and a location solution for at least one of the nodes in the WLAN.

Abstract: In one embodiment, a first set of digital data (e.g., an image) is tested for the presence of a certain feature (e.g., a certain face), yielding one of two outcomes (e.g., not-present, or present). If the testing yields the first outcome, no additional testing is performed. If, however, the testing yields the second outcome, further testing is performed to further check this outcome. Such further testing is performed on a second set of digital data that is based on, but different from, the first set of data. Only if the original testing and the further testing both yield the same second outcome is it treated as a valid result. A variety of other features and arrangements are also detailed.

Abstract: Directional albedo of a particular article, such as an identity card, is measured and stored. When the article is later presented, it can be confirmed to be the same particular article by re-measuring the albedo function, and checking for correspondence against the earlier-stored data. The re-measuring can be performed through us of a handheld optical device, such as a camera-equipped cell phone. The albedo function can serve as random key data in a variety of cryptographic applications. The function can be changed during the life of the article. A variety of other features are also detailed.

Abstract: Directional albedo of a particular article, such as an identity card, is measured and stored. When the article is later presented, it can be confirmed to be the same particular article by re-measuring the albedo function, and checking for correspondence against the earlier-stored data. The re-measuring can be performed through us of a handheld optical device, such as a camera-equipped cell phone. The albedo function can serve as random key data in a variety of cryptographic applications. The function can be changed during the life of the article. A variety of other features are also detailed.

Abstract: Information is encoded in an image signal by exploiting spectral differences between colors that appear the same when rendered. These spectral differences are detected using image sensing that discerns the spectral differences. Spectral difference detection methods include using sensor-synchronized spectrally-structured-light imaging, 3D sensors, imaging spectrophotometers, and higher resolution Bayer pattern capture relative to resolution of patches used to convey a spectral difference signal.

Abstract: One arrangement concerns a portable device (e.g., a smartphone) that executes plural recognition agents, such as agents that perform fingerprint-based object recognition, fingerprint-based audio recognition, barcode reading, watermark decoding, etc. Each of the agents reads from and writes to a blackboard data structure, to which camera and microphone sensors also post their data. Queues of stored sensor data are thus available for the agents to process. In some arrangements, the agents also post—to the blackboard—estimates of the resource costs required to perform certain functions, and estimates of the quality of results that may be achieved by such functions. This allows the system to make informed decisions about how to deploy the device's limited resources (battery, processing cycles, network bandwidth, etc.). A great variety of other features and arrangements are also detailed.

Abstract: A smart phone senses audio and/or imagery from a surrounding environment, and acts to provide graphical user interfaces and toggling discovery modes.

Abstract: Discerning small, weak features (“specks”) from imagery can be critical in early-stage cancer detection and other applications. In one aspect, the presence of a speck is judged from a large set of “votes” about whether a point in the imagery has a value above or below its neighbors. Hundreds or thousands or more votes can be gathered from one or more images, to thereby—in the aggregate—tend to confirm or refute the presence of a speck at a particular location. Votes can be based on simple pixel differences, e.g., between a pixel at the center of a 7×7 pixel image excerpt, and each of 48 other pixels in the excerpt. More sophisticated methods can employ analyses of triads, quads, and rings, and kernel-based Markov Random Field frameworks, to roll-up to a final conclusion. A great number of other features and arrangements are also detailed. The technology is particularly illustrated in the context of detecting exoplanets from astronomical imagery of remote star systems.

Abstract: A smart phone senses audio and/or imagery from a surrounding environment, and acts to provide graphical user interfaces and toggling discovery modes.

Abstract: Cell phones and other portable devices are equipped with a variety of technologies by which existing functionality is improved, and new functionality is provided. Some aspects relate to imaging architectures, in which a cell phone's image sensor is one in a chain of stages that successively act on instructions/data, to capture and later process imagery. Other aspects relate to distribution of processing tasks between the device and remote resources (“the cloud”). Elemental image processing, such as filtering and edge detection—and even some simpler template matching operations—may be performed on the cell phone. Other operations are referred out to remote service providers. The remote service providers can be identified using techniques such as a reverse auction, though which they compete for processing tasks. Other aspects of the disclosed technologies relate to visual search capabilities, and determining appropriate actions responsive to different image inputs.

Abstract: Methods and arrangements involving portable user devices such smartphones and wearable electronic devices are disclosed, as well as other devices and sensors distributed within an ambient environment. Some arrangements enable a user to perform an object recognition process in a computationally- and time-efficient manner. Other arrangements enable users and other entities to, either individually or cooperatively, register or enroll physical objects into one or more object registries on which an object recognition process can be performed. Still other arrangements enable users and other entities to, either individually or cooperatively, associate registered or enrolled objects with one or more items of metadata. A great variety of other features and arrangements are also detailed.

Abstract: Mobile phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some aspects relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others concern user interface improvements. Other aspects relate to imaging architectures, in which a mobile phone's image sensor is one in a chain of stages that successively act on packetized instructions/data, to capture and later process imagery. Still other aspects relate to distribution of processing tasks between the mobile device and remote resources (“the cloud”). Elemental image processing (e.g., simple filtering and edge detection) can be performed on the mobile phone, while other operations can be referred out to remote service providers.

Abstract: Reference imagery of dermatological conditions is compiled in a crowd-sourced database (contributed by clinicians and/or the lay public), together with associated diagnosis information. A user later submits a query image to the system (e.g., captured with a smartphone). Image-based derivatives for the query image are determined (e.g., color histograms, FFT-based metrics, etc.), and are compared against similar derivatives computed from the reference imagery. This comparison identifies diseases that are not consistent with the query image, and such information is reported to the user. Depending on the size of the database, and the specificity of the data, 90% or more of candidate conditions may be effectively ruled-out, possibly sparing the user from expensive and painful biopsy procedures, and granting some peace of mind (e.g., knowledge that an emerging pattern of small lesions on a forearm is probably not caused by shingles, bedbugs, malaria or AIDS).

Abstract: In one particular arrangement, a smartphone camera is moved by a user to capture dermatologic imagery from a variety of viewpoints. When the user thereafter holds the phone in a particular pose (e.g., with the display inclined upwardly, and with a display edge oriented substantially horizontally), the device switches to a display mode—presenting information derived from the earlier-captured dermatologic imagery. The device thus switches automatically between data collection and data presentation modes, based on pose and motion. A great variety of other features and arrangements are also detailed.

Abstract: Audio sounds are captured from a subject's body, e.g., using a smartphone or a worn array of microphones. Plural features are derived from the captured audio, and serve as fingerprint information. One such feature may be a time interval over which a threshold part of spectral energy in the audio is expressed. Another may be a frequency bandwidth within which a second threshold part of the spectral energy is expressed. Such fingerprint information is provided to a knowledge base that contains reference fingerprint data and associated metadata. The knowledge base matches the fingerprint with reference fingerprint data, and provides associated metadata in return—which can comprise diagnostic information related to the captured sounds. In some arrangements, an audio signal or pressure waveform stimulates the body at one location, and is sensed at another, to discern information about the intervening transmission medium. A great variety of other features and arrangements are also detailed.

Abstract: Computer-aided dermatological analysis requires accurate color data. Color accuracy can be improved by compensating captured imagery based on reference color data. In one particular arrangement, reference color data is acquired from blood. In another arrangement, imagery captured from a banknote is used as reference data. A great variety of other features and arrangements are also detailed.

Abstract: In one arrangement, a smartphone camera gathers skin imagery while controlled spectral illumination is emitted from the smartphone display. In a particular embodiment, differently colored bands move across a darkened screen to illuminate the skin from different angles as plural images are being captured. The collection of imagery from different viewing angles, with different spectral illumination, and different illumination angles, can provide imagery (including composite imagery) useful in manual or automated dermoscopic analysis. A great variety of other features and arrangements are also detailed.