Abstract: An earphone plug for receiving sound signals, having a first headphone cord connected to the earphone plug having a first length, and a second headphone cord connected to the earphone plug having a second length is provided. A first earphone body connected to the first headphone cord is provided for converting the sound signals to audible sounds. A second earphone body, connected to the second headphone cord, is provided for converting the sound signals to audible sounds. An attachment mechanism coupled to at least a portion of the first headphone cord or the second headphone cord for securing the earphone to an article of clothing.

Abstract: Acoustic loudspeaker comprising: a movable membrane; a source of constant magnetic field, a coil mechanically secured to said membrane and interacting with the magnetic field so as to displace the membrane, when it is traversed by an alternating current, characterized in that the membrane carries the coil at its periphery, and in that the magnetic field source is formed by a set of at least one magnetized element disposed at the periphery of said membrane, around the coil, the magnetic field generated by said at least one magnetized element being in a plane parallel to the membrane.

Abstract: Coaxial two-way or more loudspeaker system comprising a low range electro-dynamic transducer and a high range transducer with compression chamber, mounted in a coaxial and frontal with respect of the low range transducer.

Abstract: According to one embodiment, there is disclosed a template cleaning apparatus to clean a template for imprint. The template includes a concave-convex pattern and a groove portion, and an image obtaining unit which obtains an image of a region including a side surface of the groove portion of the template. The apparatus further includes a cleaning time determination (CTD) unit having a function to determine cleaning time of the template. The function includes determining the cleaning time by comparing the image obtained by the image obtaining unit with a previously obtained reference image. The apparatus further includes a cleaning unit which cleans the template, based on the cleaning time determined by the CTD unit.

Abstract: Signatures that can be used to identify video and audio content are generated from the content by generating measures of dissimilarity between features of corresponding groups of pixels in frames of video content and by generating low-resolution time-frequency representations of audio segments. The signatures are generated by applying a hash function to intermediate values derived from the measures of dissimilarity and to the low-resolution time-frequency representations. The generated signatures may be used in a variety of applications such as restoring synchronization between video and audio content streams and identifying copies of original video and audio content. The generated signatures can provide reliable identifications despite intentional and unintentional modifications to the content.

Abstract: An apparatus and method for video fingerprinting are provided. The method includes, for each frame of a video sequence including a plurality of frames, removing a portion of the frame, dividing a remaining portion of the frame into blocks, dividing each block into sub-blocks, computing a block level feature as a mean of pixels in each sub-block within the block, concatenating all block level features in the frame, and concatenating features of all frames in the video sequence.

Abstract: The present invention provides methods and systems to protect an organization's secure image information from unauthorized disclosure. In one embodiment, methods and systems to generate image fingerprints are provided. The fingerprints are generated for each feature point of an image data. Because the fingerprints take into account the neighborhood features around each feature point, the image fingerprints are robust against derivative images where the original image may have been altered. Methods and systems to maintain a fingerprint database for an organization's secure image data is also provided. In one embodiment, client fingerprints are generated for image data that a user intends to transmit outside of the organization. In some embodiments, suitable security actions are initiated if any of the client fingerprints match any of the fingerprints in the fingerprint database.

Abstract: Content fingerprints and watermarks are combined in various ways for content identification applications. Fingerprints are used to identify content generally while watermarks provide more detailed localization of parts within the content, and vice versa. Fingerprint techniques are further used for signal synchronization and other pre-processing steps to assist in digital watermark decoding. A variety of fingerprint/watermark techniques identify characteristics of the channel of content from content samples.

Abstract: System and method for detecting cloud shadows over water from ocean color imagery received from remote sensors.

Abstract: The homography between captured images of a planar object is determined and decomposed into at least one possible solution, and typically at least two ambiguous solutions. The removal of the ambiguity between the two solutions, or validation of a single solution, is performed using a viewing angle range. The viewing angle range may be used by comparing the viewing angle range to the orientation of each solution as derived from the rotation matrix resulting from the homography decomposition. Any solution with an orientation outside the viewing angle range may be eliminated as a solution.

Abstract: Light is allowed to be incident from above wells provided on a microplate M and the light transmitted to the lower surface is received to obtain an original image of the wells (Step S101). Detection target areas in the original image are specified by an appropriate image processing (Step S102), and peripheral areas as backgrounds surrounding the respective detection target areas are specified (Step S103). By calculating a density value of the detection target area Ri using luminance information of the detection target area Ri and that of the peripheral area Si surrounding this detection target area Ri for each detection target area Ri (Steps S105, S106), the influence of a well wall surface reflected on the background is eliminated.

Abstract: Feature extraction includes extracting features from signals of a plurality of sensors of a sensor array, including, for each sensor, obtaining a signal of the sensor corresponding to responses of the sensor during one or more exposures to samples, computing a baseline function from the signal, and computing the features based on the baseline function and values corresponding to responses of the sensor during each exposure. Feature vectors are formed from the features of the sensors. The features in each feature vector correspond to the same exposure. At least one of computing the baseline function by interpolating baseline values corresponding to responses of the sensor prior to each exposure, and forming the feature vectors by combining features of at least one sensor with features of at least one redundant sensor of the sensor array in the feature vectors is performed.

Abstract: An image corresponding to a pattern having a first size is detected from a first detection region in an acquired, first image, and an image corresponding to a pattern having a second size is detected from a second detection region different from the first detection region in the first image.

Abstract: An image recognizing apparatus is equipped with: a detecting unit configured to detect, from an input image, a candidate area for a target of recognition, based on a likelihood of a partial area in the input image; an extracting unit configured to extract, from a plurality of candidate areas detected by the detecting unit, a set of the candidate areas which are in an overlapping relation; a classifying unit configured to classify an overlapping state of the set of the candidate areas; and a discriminating unit configured to discriminate whether or not the respective candidate areas are the target of recognition, based on the overlapping state of the set of the candidate areas and the respective likelihoods of the candidate areas.

Abstract: A method is provided for detecting a body part in a video stream from a mobile device. A video stream of a human subject is received from a camera connected to the mobile device. The video stream has frames. A first frame of the video stream is identified for processing. This first frame is then partitioned into observation windows, each observation window having pixels. In each observation window, non-skin-toned pixels are eliminated; and the remaining pixels are compared to determine a degree of entropy of the pixels in the observation window. In any observation window having a degree of entropy above a predetermined threshold, a bounded area is made around the region of high entropy pixels. The consistency of the entropy is analyzed in the bounded area. If the bounded area has inconsistently high entropy, a body part is determined to be detected at that bounded area.

Abstract: Methods and systems for object tracking are disclosed in which the bandwidth of a “slow” tracking system (e.g., an optical tracking system) is augmented with sensor data generated by a “fast” tracking system (e.g., an inertial tracking system). The tracking data generated by the respective systems can be used to estimate and/or predict a position, velocity, and orientation of a tracked object that can be updated at the sample rate of the “fast” tracking system. The methods and systems disclosed herein generally involve an estimation algorithm that operates on raw sensor data (e.g., two-dimensional pixel coordinates in a captured image) as opposed to first processing and/or calculating object position and orientation using a triangulation or “back projection” algorithm.

Abstract: A plurality of candidate points are extracted from image data. The plurality of candidate points are normalized, and a set of representative points composing form model that is most similar to set form is selected from the plurality of candidate points. Further, the candidate points and the form model are compared with each other, and correction is performed by adding a region forming structure or by deleting a region, or the like. Accordingly, the structure is detected in image data.

Abstract: There is provided an image processing device including: a data storage unit that stores object identification data for identifying an object operable by a user and feature data indicating a feature of appearance of each object; an environment map storage unit that stores an environment map representing a position of one or more objects existing in a real space and generated based on an input image obtained by imaging the real space using an imaging device and the feature data stored in the data storage unit; and a selecting unit that selects at least one object recognized as being operable based on the object identification data, out of the objects included in the environment map stored in the environment map storage unit, as a candidate object being a possible operation target by a user.

Abstract: An image processing device comprises: image display means which displays at least one of transformation target images containing an object of interest; first reference point receiving/determining means which receives information on first reference point candidates according to a user operation, receives according to a user operation a determination signal targeted at the first reference point candidates displayed on the transformation target image based on the information on the first reference point candidates, and determines first reference points based on the information on the first reference point candidates targeted by the received determination signal; second reference point receiving/determining means which determines second reference points by receiving information on the second reference points; and geometric transformation means which outputs a transformed image by conducting geometric transformation to the transformation target image based on the first reference points determined by the first refe

Abstract: Method for efficient computation of wave equation migration angle gathers by using multiple imaging conditions. Common reflection angle or common azimuth gathers or gathers including both common reflection angles and common azimuth angles are produced as the data are migrated. In the course of either wave equation migration or reverse time migration, the pressures and particle motion velocities that need to be computed are sufficient to also compute the Poynting vector pointing in the direction of source-side (35) or receiver-side (37) wavefield propagation. From that, the reflection and azimuth angles can be computed (38). The seismic images can then be stored in the appropriate angle bins, from which common reflection angle or azimuth data volumes can be assembled (39).

Abstract: A computer-implemented image analysis process, including: accessing image data representing an image including an animal object representing an animal; selecting one more start points on a boundary of the animal object using an intensity gradient of the image; and generating boundary data, representing at least a portion of the boundary, starting at each of the selected one or more start points, using the intensity gradient.

Abstract: The present disclosure provides an electronic device and a method of turning on or unlocking an electronic device. The method includes steps: controlling the capturing unit to capture a predetermined number of facial images in response to an input for turning on or unlocking the electronic device. Acquiring a clear facial image from the predetermined number of facial images. Performing an image processing for the clear facial image to obtain a facial feature of the clear facial image; and if there is one facial feature in the stored at least one facial image matching with the facial feature of the clear facial image in the storage unit, turning on or unlocking the electronic device.

Abstract: Systems and methods acquire and/or generate multiple different images of the same biometric identity, identify specific instances of biometric features in each of the different images, and merge the identified specific instances of biometric features into a data record that provides a digital representation of the biometric identity. Examples of biometric identities include fingerprints, handprints, palm prints, and thumbprints. In one embodiment, a counter is associated with each specific instance of a biometric feature found in the multiple images. Specific instances of biometric features found most frequently have high counts and are indicative of true identifications; those with low counts are indicative of false identifications. A threshold distinguishes between true and false identifications. Those specific instances with counts below the threshold are excluded when the digital representation of the biometric identity is generated.

Abstract: Systems and methods for determine a centerline of a tubular structure from volumetric data of vessels where a contrast agent was injected into the blood stream to enhance the imagery for centerline. An active contour model may be applied to determine contours of the vessel defined within image data by normalizing the image data about a starting point. A snake may be initialized a first time, where the snake defines a set of points that represent a spline within the vessel. Image forces that act on the snake to pull the snake toward a contour of the vessel may be calculated and iteratively applied in a minimization process to determine the contour of the vessel. Optionally, a Gaussian smoothing operation may be performed.

Abstract: A medical image processing apparatus includes: a feature value calculation portion that, for each pixel of an image, calculates a feature value that is used when extracting a linear structure; a judgment portion that, based on a result of a comparison between the feature value of a pixel of interest and feature values of a plurality of pixels located in the vicinity of the pixel of interest, judges whether the pixel of interest is a linear structure pixel or is a nonlinear structure candidate pixel; and a correction portion that identifies a pixel that is determined to be a linear structure pixel that is in the vicinity of the nonlinear structure candidate pixel, calculates information with respect to the identified linear structure candidate pixel and determines whether to make the nonlinear structure candidate pixel the nonlinear structure pixel or the linear structure pixel based on the calculated information.

Abstract: A system for handling a specimen image is disclosed. An image input (1) is configured to receive a body image representing at least a portion of a living body and a specimen image representing a dissected portion of the living body. An alignment unit (2) is configured to compute an alignment of the specimen image with the body image, based on image content of the specimen image and/or the body image. A border detector (3) is operatively connected to the alignment unit (2) and configured to detect at least part of an outer border of the dissected portion in the specimen image.

Abstract: Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Abstract: Automatic prostate localization in T2-weighted MR images facilitate labor-intensive cancer imaging techniques. Methods and systems to accurately segment the prostate gland in MR images are provided and address large variations in prostate anatomy and disease, intensity inhomogeneities, and artifacts induced by endorectal coils. A center of the prostate is automatically detected with a boosted classifier trained on intensity based multi-level Gaussian Mixture Model Expectation Maximization (GMM-EM) segmentations of the raw MR images. A shape model is used in conjunction with Multi-Label Random Walker (MLRW) to constrain the seeding process within MLRW.

Abstract: A method for reformatting image data includes obtaining volumetric image data indicative of an anatomical structure of interest, identifying a surface of interest of the anatomical structure of interest in the volumetric image data, identifying a thickness for a sub-volume of interest of the volumetric image data, shaping the sub-volume of interest such that at least one of its sides follows the surface of interest, and generating, via a processor, a maximum intensity projection (MIP) or direct volume rendering (DVR) based on the identified surface of interest and the shaped sub-volume of interest.

Abstract: In various embodiments, methods and apparatus are provided for automated selection of features of cells useful for classifying cell phenotype. The methods include determining a signal-to-noise ratio (S/N) for each of a plurality of pairs of features, rather than S/N for individual features. The approach is capable of quickly identifying a small set of features of imaged cells that are most relevant for classification of a desired cell phenotype from among a very large number of features. The small group of relevant features can then be used to more efficiently and more accurately classify phenotype of unidentified cells.

Abstract: Methods and systems for determining design coordinates for defects detected on a wafer are provided. One method includes aligning a design for a wafer to defect review tool images for defects detected in multiple swaths on the wafer by an inspection tool, determining a position of each of the defects in design coordinates based on results of the aligning, separately determining a defect position offset for each of the multiple swaths based on the swath in which each of the defects was detected (swath correction factor), the design coordinates for each of the defects, and a position for each of the defects determined by the inspection tool, and determining design coordinates for the other defects detected in the multiple swaths by the inspection tool by applying the appropriate swath correction factor to those defects.

Abstract: A method and an apparatus for determining a confidence value of a disparity estimate for a pixel or a group of pixels of a selected image of at least two stereo images are described, the confidence value being a measure for an improved reliability value of the disparity estimate for the pixel or the group of pixels. First an initial reliability value of the disparity estimate for the pixel or the group of pixels is determined, wherein the reliability is one of at least reliable and unreliable. Then a distance of the pixel or the group of pixels to a nearest pixel or group of pixels with an unreliable disparity estimate is determined. Finally, the confidence value of the disparity estimate for the pixel or the group of pixels is obtained from the determined distance.

Abstract: A training system, training method, and a system and method of use of a trained classification system are provided. A classifier may be trained with a first “cheap” view but not using a second “costly” view of each of the training samples, which is not available at test time. The two views of samples are each defined in a respective original feature space. An embedding function is learned for embedding at least the first view of the training samples into a common feature space in which the second view can also be embedded or is the same as the second view original feature space. Labeled training samples (first view only) for training the classifier are embedded into the common feature space using the learned embedding function. The trained classifier can be used to predict labels for test samples for which the first view has been embedded in the common feature space with the embedding function.

Abstract: Systems and method are provided for adjusting certain pixel values in an image. In an embodiment of the invention, an average pixel value of pixels at given distances from a selected pixel are examined to determine if the pixel is in a high-contrast area. If the pixel is in a smooth color gradient transition area, the pixel value may be adjusted in some embodiments using an additional dither or dither pattern to reduce differences between the pixel values of the selected pixel and the additional average pixel values exceeding the lower threshold.

Abstract: Provided is an image processing apparatus including a calculation unit that calculates, as a foreground feature vector, a feature vector indicating a difference between colors of pixels in a predetermined region including a target pixel and a color of the target pixel, using each of the pixels as the target pixel, a determination unit that determines whether to integrate two pixels or regions to be integrated, depending on similarity of the foreground feature vectors with respect to the two pixels or regions, and an integration unit that integrates the two pixels or regions determined to be integrated by the determination unit.

Abstract: Methods and systems for evaluating an imager that produces bi-chrome images from a scanner or a digital imaging device, the bi-chrome images having pixels of a first and second color. In one embodiment, a method includes generating an image with a hand-held imaging device, the image having pixels of a first color and a second color, analyzing the image to determine information about particles of the first and second color contained in the image, each particle comprising contiguous pixels of the same color, the particle information comprising information on first and second color particle size and count, and determining if the image is unacceptable based on predetermined objective criteria and the particle information.

Abstract: An embodiment of a method for reducing chroma noise in digital image data and of a corresponding image processor. Chrominance components are subjected to low-pass filtering. The strength of the low-pass filtering is modulated in accordance with the dynamic range of the luminance signal and the dynamic range of each of the two chrominance signals in order to avoid color bleeding at image-object edges. Moreover, the low-pass filtering is selectively applied to pixels with similar luminance and chrominance values only. A combination of down-sampling and up-sampling units is employed so that comparatively small filter kernels may be used for removing chroma noise with low spatial frequency.

Abstract: A method for the reduction of noise in an image including identifying neighboring pixel values in pixels proximate to a subject pixel; comparing the neighboring pixel values to a preset tolerance range; using neighboring pixel values within the tolerance range to calculate a pixel intensity correction value; and applying the pixel intensity value to the subject pixel.

Abstract: A system and method for enhancing a content file is disclosed. The system comprises a histogram module, a contrast stretching module and a brightness module. The histogram module generates a histogram including data that describes one or more pixel intensities for one or more channels included in a content file. The contrast stretching module adjusts the one or more pixel intensities for the one or more channels included in the content file based at least in part on the histogram. The brightness module is communicatively coupled to the contrast stretching module for determining whether a brightness level for the content file is within a range describing one or more acceptable brightness levels. The brightness module adjusts the brightness level for the content file responsive to determining that the brightness level for the content file is outside the range.

Abstract: An image conversion parameter calculation device capable of accurately calculating a conversion parameter for image alignment with a processing amount that does not depend on a size of an image to be aligned is provided. Pixel selection element 2 randomly selects a pixel of a predetermined number or pixel of not more than the predetermined number from a first image. Parameter derivation element 6 derives a conversion parameter by performing processing for selected pixels which are the pixels selected by the pixel selection element, the conversion parameter being a parameter for converting, to the first image, a second image that is subject to image alignment with the first image.

Abstract: An apparatus and a method for processing image feature descriptor are disclosed. The image feature descriptor processing apparatus comprises a header storing unit, a vector storing unit, a feature capture unit, a distribute unit, and a memory controller. The feature capture unit captures image feature descriptors. The distribute unit generates a header base address, a vector base address, headers, and vectors according to the image feature descriptors. The memory controller continuously writes the headers to the header storage unit according to the header base address and continuously writes the vectors to the vector storage unit according to the vector base address.

Abstract: In an interpolation image generation apparatus, an input unit acquires photographed images obtained from viewpoints and imaging setting information thereof, the EPI generation unit generates an EPI from the images, an angle estimation unit estimates an angle of a straight line to which each EPI actual pixel corresponds on the EPI, an interpolation image setting unit places an interpolation image on the EPI, a correspondence detection unit detects correspondence between an actual pixel and a pixel of the interpolation image (interpolation pixel), and the correspondence detection unit evaluates likelihood of correspondence relationship between the actual pixel and the interpolation pixel, and a pixel value addition unit adds a pixel value of the interpolation pixel on the basis of the likelihood of the correspondence relationship, thereby generating an interpolation image.

Abstract: An index detecting section detects an index in a physical space, from a captured image obtained by an imaging apparatus. An erroneous-detection prevention processing section performs erroneous-detection prevention processing, based on information relating to image coordinates of a detected index. An image output section outputs, to a display device, an image having been subjected to the erroneous-detection prevention processing. This prevents an image displayed on the display device from being mistaken for a real index when the display device is in the field of view of the imaging apparatus.

Abstract: An information processing apparatus comprising a setting unit configured to set a plurality of local regions on an image; an extraction unit configured to extract feature amounts from the respective local regions; a calculation unit configured to calculate dissimilarities between the local regions based on probability densities for the respective feature amounts; and an integration unit configured to integrate the plurality of local regions as region groups based on the dissimilarities.

Abstract: An object control device includes an object of interest specifying unit configured to specify an object of interest to obtain position information on the object of interest, an obstacle determining unit configured to determine whether there is an obstacle between the object of interest and the object, and a time measuring unit configured to measure a period after determining that there is the obstacle, and a holding unit configured to hold position information of the object of interest when the period reaches a predetermined period, and an object action control unit configured to control a direction of a part of the object, based on the position information obtained by the object of interest specifying unit before the period reaches the predetermined period, and based on the position information on the object of interest held in the holding unit after the period reaches the predetermined period.

Abstract: An object of the present invention is to encode and decode image information more efficiently by generating an appropriate predictive signal. The image encoding device of the present invention comprises an input section 201 for inputting an input image constituting an encoding target; a reference image accumulation section 202 for accumulating a reference image; a reference image accompanying information accumulation section 203 for accumulating reference image accompanying information which accompanies the reference image; an encoding section 206 for modifying the reference image and the reference image accompanying information in accordance with the input image, generating a predictive signal for the input image, and encoding the input image; and an output section 209 for outputting, as encoded data, compressed data obtained by encoding by the encoding means together with modification method information indicating a modification method for the reference image.

Abstract: An embodiment in accordance with the present invention provides a system and method for image analysis and processing. The present invention provides a software package for processing AFM data. More particularly it can be used for characterizing carbon nanotubes found within AFM images, though it does offer editing features that are general in nature. Its features are split amongst five menus, one button, and four data panels. The software package can be used to determine physical characteristics related to the imaged subject, such as, for instance length data for imaged carbon nanotubes.

Abstract: A method and gem pattern matching technique to analyze a target gemstone by analyzing a pattern created by transmitting a light source such as a laser beam through the gemstone to create a visual optical pattern and comparing the pattern to a database of known gemstone patterns to determine the percentage likelihood that the target gemstone will match a gemstone in the database. The matching is based on the weight of the heaviest spot in the pattern and its location in the gemstone image and comparing it to the weight and location of the heaviest spots in each gemstone image in the database to determine a percentage matching.

Abstract: The disclosure is related to a system and method for learning robust clothing clustering based on a cluster ensemble technique applied to the clothing features of images to improve clustering of images. Different types of clothing features that are complementary to each other are computed to provide extensive description of the clothing in the images. Multiple partitions are computed based on the clothing features to generate a cluster ensemble set. A consensus function is applied to the multiple partitions to generate a final clothing consensus clustering that encompasses the information contained in the multiple partitions. A system and method are disclosed for clustering images based on the clothing of one or more persons in the images.

Abstract: A compressed image, for which a desired SSIM value is obtained, is acquired when irreversible compression is performed. Specifically, a quadratic curve G2 is defined. Next, a compression ratio P4 is calculated. An image is irreversibly compressed at the compression ratio P4, the compressed image is decoded and an SSIM value S5 is calculated. If the calculated SSIM value S5 is outside an allowable range of the target SSIM value, then the quadratic curve G2 is corrected in such a manner that it will pass through an intersection C4 between the compression ratio P4 and the SSIM value S5, whereby a quadratic curve G3 is obtained.