Abstract: A method of classifying images includes extracting parameters from each of the images. The parameters of each image is quantized. Once the quantization data of each image is obtained, each image is classified according to quantization data.

Abstract: Systems and methods track one or more points between images. A point for tracking may be selected, at least in part, on a determination of how discriminable the point is relative to other points in a region containing the point. A point of an image being tracked may be located in another image by matching a patch containing the point with another patch of the other image. A search for a matching patch may be focused in a region that is determined based at least in part on an estimate of movement of the point between images. Points may be tracked across multiple images. If an ability to track one or more points is lost, information about the points being tracked may be used to relocate the points in another image.

Abstract: Methods, systems, and computer-readable media for detecting duplicate deposit items at a point of capture are presented. In some embodiments, a computing platform may receive image data of a deposit item presented for deposit. Subsequently, the computing platform may obtain magnetic ink character recognition (MICR) information for the deposit item. Then, the computing platform may extract information from one or more visible fields of the deposit item. Next, the computing platform may compare the MICR information and the information extracted from the one or more visible fields with item history information to determine a confidence score indicative of whether the deposit item is a duplicate of a previously-deposited item. If the confidence score is less than a threshold, the computing platform may reject the deposit item at the point of capture. Alternatively, if the confidence score is not less than the threshold, the computing platform may accept the deposit item.

Abstract: Disclosed are methods and apparatus for inspecting an extreme ultraviolet (EUV) reticle is disclosed. An inspection tool for detecting electromagnetic waveforms is used to obtain a phase defect map for the EUV reticle before a pattern is formed on the EUV reticle, and the phase defect map identifies a position of each phase defect on the EUV reticle. After the pattern is formed on the EUV reticle, a charged particle tool is used to obtain an image of each reticle portion that is proximate to each position of each phase defect as identified in the phase defect map. The phase defect map and one or images of each reticle portion that is proximate to each position of each phase defect are displayed or stored so as to facilitate analysis of whether to repair or discard the EUV reticle.

Abstract: Image scaling disclosed herein comprises receiving an image from an image capturing device and partitioning an image into at least one image tile using a partitioning module. A determination is made if the image tile requires slow scan scaling and/or fast scan scaling. The image tile is subject to slow scan scaling. The image tile is then transposed, scaled in the fast scan direction, and then again transposed to an original orientation. The tile is reassembled into a scaled image and may be rendered by a rendering device.

Abstract: An image sequence acquisition section acquires an image sequence including a plurality of images. A processing section performs an image summarization process that acquires a summary image sequence based on first and second deletion determination processes that delete some of the images included in the acquired image sequence. The processing section sets an attention image sequence including one at least one attention image included in the plurality of images, selects a first reference image from the attention image sequence, selects a first determination target image from the plurality of images, and performs the first deletion determination process that determines whether the first determination target image can be deleted based on first deformation information that represents deformation between the first reference image and the first determination target image.

Abstract: In one aspect, a computer implemented method of motion capture, the method includes tracking the motion of a dynamic object bearing a pattern configured such that a first portion of the patterns is tracked at a first resolution and a second portion of the pattern is tracked at a second resolution. The method further includes causing data representing the motion to be stored to a computer readable medium.

Abstract: Provided are a color moire reducing method, a color moire reducing apparatus, and an image processing apparatus. The color moire reducing method includes calculating a plurality of local color mean values around a pixel in a selected region of a current image, calculating difference values between the local color mean values and a maximum difference value from among the difference values, and setting a moire correction weight to the pixel on the basis of the maximum difference value.

Abstract: A “Food Logger” provides various approaches for learning or training one or more image-based models (referred to herein as “meal models”) of nutritional content of meals. This training is based on one or more datasets of images of meals in combination with “meal features” that describe various parameters of the meal. Examples of meal features include, but are not limited to, food type, meal contents, portion size, nutritional content (e.g., calories, vitamins, minerals, carbohydrates, protein, salt, etc.), food source (e.g., specific restaurants or restaurant chains, grocery stores, particular pre-packaged foods, school meals, meals prepared at home, etc.). Given the trained models, the Food Logger automatically provides estimates of nutritional information based on automated recognition of new images of meals provided by (or for) the user. This nutritional information is then used to enable a wide range of user-centric interactions relating to food consumed by individual users.

Abstract: A method for rendering an image from ultrasound image data includes dividing the ultrasound image data into at least a first group of voxels and a second group of voxels, based on comparing voxel echo intensity to a threshold value. The method further includes processing the first group of voxels according to a first protocol and processing the second group of voxels according to a second protocol. The method further includes generating an image that includes both the first group of processed voxels and the second group of processed voxels to enhance realism of the rendered image.

Abstract: A method and apparatus for generating an organ image are provided. An organ image generating method involves: receiving image data of a medical image of a subject; extracting an image of an organ from the medical image; receiving image data of a generic image of the organ; and generating image data of an organ image of the subject from the generic image of the organ and the extracted image of the organ.

Abstract: The disclosure relates generally to geographic-based signal detection. One claim recites an apparatus comprising: an input for receiving a signal from a cell phone; an electronic processor for determining, based at least in part on the signal, whether the cell phone is physically located in a predetermined home area; and upon a condition of not being in the predetermined home area, communicating a machine-readable code detector to the cell phone for use as its primary machine-readable code detector to detect machine-readable code while outside of its predetermined home area. Of course, other claims and combinations are provided as well.

Abstract: Various embodiments are generally directed to the provision and use of multiple person biometric authentication systems. An apparatus including a processor element and logic executable by the processor component is disclosed. The logic is configured to cause the apparatus to receive information including an indication of a plurality of biometric measurements and generate a combined biometric indicator based in part on the plurality of biometric measurements. The combined biometric indicator can be generated using fuzzy hashing techniques.

Abstract: Techniques are provided for generating a 3-Dimensional (3D) reconstruction of a handheld object. An example method may include receiving 3D image frames of the object from a static depth camera, each frame including a color image and a depth map. Each of the frames is associated with an updated pose of the object during scanning. The method may also include extracting a segment of each frame corresponding to the object and the hand; isolating the hand from each extracted segment; and filtering each frame by removing regions of the frame outside of the extracted segment and removing regions of the frame corresponding to the isolated hand. The method may further include calculating the updated object pose in each filtered frame; and calculating a 3D position for each depth pixel from the depth map of each filtered frame based on the updated object pose associated with that filtered frame.

Abstract: A method of operating an electronic device is provided. The method of operating an electronic device includes displaying an image of a first resolution, determining at least a partial region of the image, and displaying an image of a second resolution corresponding to the partial region.

Abstract: An image processing apparatus includes an alignment unit configured to align a first fundus oculi image that is an aberration-corrected image of an eye being examined and a second fundus oculi image having a larger view angle and a lower resolution than the first fundus oculi image, by using a third fundus oculi image having a smaller view angle and a higher resolution than the second fundus oculi image; a distance acquisition unit configured to acquire a distance from a macula lutea of the eye being examined to a certain position in the first fundus oculi image aligned by the alignment unit; and an evaluation unit configured to evaluate the state of the eye being examined from the distance and information concerning photoreceptor cells included in the first fundus oculi image.

Abstract: The invention provides median image media quality enhancer. The image media is fed into a computing device which is essentially a burst of images or video to be enhanced. Each frame within the image media is identically exposed and hence neighboring images are used to enhance quality of the image media. For each of the neighboring frames, each pixel of these neighboring frame is moved in order to correspond to the image media. Once all the neighboring frames are processed, these are stacked in order to increase signal to noise ratio to create a composite image. This reduces unwanted spots and luminosity fluctuation from the digitized video.

Abstract: According to one embodiment, an image processing apparatus includes a dividing unit, a calculating unit, a determining unit, and an output unit. The dividing unit is configured to divide an image into a plurality of regions. The calculating unit is configured to calculate a standard deviation and an entropy per region divided by the dividing unit based on tone information of pixels comprising each region, and calculate a ratio between the standard deviation and the entropy. The determining unit is configured to determine a region in which the ratio exceeds a reference value. The output unit is configured to output information based on a determination result obtained by the determining unit.

Abstract: Images of an environment that are captured from two or more imaging devices may be captured and evaluated in order to identify a state of the environment, or an interaction that placed the environment in the state. The content of the images may be analyzed in order to recognize observed information or data expressed therein. The information or data may be associated with a given state according to one or more observation functions, and the state may be used to identify an action according to one or more transition functions. The observation function uses conditional probabilities to transfer the probability of making an observation by one imaging device to the observation made by the other imaging device. The observation functions and the transition functions may be derived based on historical training data including clips that are labeled to identify states or interactions expressed therein.

Abstract: A method includes separating image data into high frequency image data and low frequency image data. The high frequency image data is separated into windows, with each window containing pixels. The low frequency image data is separated into windows corresponding respectively to the plurality of windows of the high frequency image data, with each window containing pixels. For each window in the high frequency image data, a number of textured pixels in the window is determined, the textured pixels being pixels that vary greatly in luminance value with respect to other pixels in the window, and a window modification is determined such that the number of textured pixels in the window is reduced. For each corresponding window in the low frequency image data, the window modification is applied, and each textured pixel in the window is corrected based upon the other pixels in the window.