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: 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: The availability of high quality imagers on smartphones and other portable devices facilitates creation of a large, crowd-sourced, image reference library that depicts skin rashes and other dermatological conditions. Some of the images are uploaded with, or later annotated with, associated diagnoses or other information (e.g., “this rash went away when I stopped drinking milk”). A user uploads a new image of an unknown skin condition to the library. Image analysis techniques are employed to identify salient similarities between features of the uploaded image, and features of images in this reference library. Given the large dataset, statistically relevant correlations emerge that identify to the user certain diagnoses that may be considered, other diagnoses that may likely be ruled-out, and/or anecdotal information about similar skin conditions from other users. Similar arrangements can employ audio and/or other physiologically-derived signals.

Abstract: A method for indoor navigation in a venue derives positioning of a mobile device based on sounds captured by the microphone of the mobile device from the ambient environment. It is particularly suited to operate on smartphones, where the sounds are captured using microphone that captures sounds in a frequency range of human hearing. The method determines a position of the mobile device in the venue based on identification of the audio signal, monitors the position of the mobile device, and generates a position based alert on an output device of the mobile device when the position of the mobile device is within a pre-determined position associated with the position based alert.

Abstract: Audio signal processing enhances audio watermark embedding and detecting processes. Audio signal processes include audio classification and adapting watermark embedding and detecting based on classification. Advances in audio watermark design include adaptive watermark signal structure data protocols, perceptual models, and insertion methods. Perceptual and robustness evaluation is integrated into audio watermark embedding to optimize audio quality relative the original signal, and to optimize robustness or data capacity. These methods are applied to audio segments in audio embedder and detector configurations to support real time operation. Feature extraction and matching are also used to adapt audio watermark embedding and detecting.

Abstract: A method for indoor navigation in a venue derives positioning of a mobile device based on sounds captured by the microphone of the mobile device from the ambient environment. It is particularly suited to operate on smartphones, where the sounds are captured using microphone that captures sounds in a frequency range of human hearing. The method determines a position of the mobile device in the venue based on identification of the audio signal, monitors the position of the mobile device, and generates a position based alert on an output device of the mobile device when the position of the mobile device is within a pre-determined position associated with the position based alert.

Abstract: A method for indoor navigation in a venue derives positioning of a mobile device based on sounds captured by the microphone of the mobile device from the ambient environment. It is particularly suited to operate on smartphones, where the sounds are captured using microphone that captures sounds in a frequency range of human hearing. The method determines a position of the mobile device in the venue based on identification of the audio signal, monitors the position of the mobile device, and generates a position based alert on an output device of the mobile device when the position of the mobile device is within a pre-determined position associated with the position based alert.

Abstract: A positioning network comprises an array of signal sources that transmit signals with unique characteristics that are detectable in signals captured through a sensor on a mobile device, such as a microphone of a mobile phone handset. Through signal processing of the captured signal, the positioning system distinguishes these characteristics to identify distinct sources and their corresponding coordinates. A position calculator takes these coordinates together with other attributes derived from the received signals from distinct sources, such as time of arrival or signal strength, to calculate coordinates of the mobile device. A layered protocol is used to introduce distinguishing characteristics in the source signals. This approach enables the use of low cost components to integrate a positioning network on equipment used for other functions, such as audio playback equipment at shopping malls and other venues where location based services are desired.