Abstract: A method for determining variations among multiple three-dimensional stone images extracorporeally and a computer program product using the method are disclosed. The method involves during a lithotripsy process performed on a human body, multiple three-dimensional stone images taken from a stone location in the human body are processed outside the human body using the following steps: using a processing unit to execute a computing process for the multiple three-dimensional stone images one by one in an order from the first taken said image to the last taken said image, wherein the computing process involves using an entropy texture equation or an inverse difference moment (IDM) texture equation to calculate a texture feature value for each said three-dimensional stone image; and when the texture feature values calculated using the entropy texture equation or the inverse difference moment (IDM) texture equation substantively stop changing, making the processing unit output a prompt signal.

Abstract: Provided herein is a computerized image reconstruction apparatus and method that includes recording projection path information and energy loss information of a plurality of particles traversing an object being imaged and determining an estimated image of the object based on the projection path information and the energy loss information sampled into a projection format. The estimated image includes an active volume defined by an enclosure border. Cost function minimization uses an Adaptive-weighted Total Variation cost function, a Penalized Weighted Least-Squares cost function, or an Alpha-Divergence cost function to update the estimated image. An iterative updating algorithm corresponding to the cost function updates the estimated image and produces a final image based on the estimated image according to a predetermined threshold.

Abstract: A user touches a touch sensitive display or otherwise provides input comprising “stroke” gestures to trace areas which are to be the subject of post-processing functions. The stroke area is highlighted and can be added to or corrected by additional stroke and “erase” gestures. Pixel objects are detected proximate to the stroke area, with a precision based on the zoom level. Stroke gesture input may be received and pixel object determination may be performed in series or in parallel.

Abstract: A method and apparatus for providing content experience service are disclosed. The apparatus includes a camera device tracking unit, a user behavior tracking unit, a real image acquisition unit, a motion information processing unit, a virtual space control unit, and a virtual multi-image generation unit. The camera device tracking unit collects camera motion information. The user behavior tracking unit collects user motion information. The real image acquisition unit photographs a space including the user, and separates a real image into a foreground and a background using a background key table. The motion information processing unit corrects the camera motion information and the user motion information. The virtual space control unit generates virtual space control information and virtual space information. The virtual multi-image generation unit generates a virtual multi-image, and provides the content experience service based on the generated virtual multi-image.

Abstract: Disclosed herein is a framework for localizing anatomical structures. In accordance with one aspect, the framework receives a learned regressor and image data of a subject. The learned regressor may be invoked to predict a first spatial metric from a seed voxel to a target anatomical structure in the image data. The learned regressor may further be invoked to predict second spatial metrics from candidate voxels to the target anatomical structure. The candidate voxels may be located around a search region defined by the first spatial metric. The candidate voxel associated with the smallest second spatial metric may then be output as a localized voxel.

Abstract: Techniques are disclosed for detecting new events in a video stream that yield improved detection efficiency in real time. For example, a method determines whether a given event is a new event in a video stream. The video stream includes a plurality of events. A first step extracts a first set of features (e.g., text features) from the given event. The first set of features is computationally less expensive to process as compared to a second set of features (e.g., image features) associated with the given event. A second step computes one or more first dissimilarity values between the given event and one or more previous events in the video stream using only the first set of features when one or more first dissimilarity criteria exist. A third step determines whether the given event is a new event based on the one or more computed first dissimilarity values.

Abstract: A method of operating an image reader typically includes: searching a digital image for nominally straight edges; characterizing the nominally straight edges in terms of length and/or direction; determining a predominant orientation of the nominally straight edges; establishing a group of edges as a function of their proximity to the center of the image; establishing a group of edges as a function of their proximity to other remaining edge positions; and transmuting a rectangle bounding those edges into a rectified image. The rectified image is typically an image that is cropped or rotated.

Abstract: A method of improving the lighting conditions of a real scene or video sequence. Digitally generated light is added to a scene for video conferencing over telecommunication networks. A virtual illumination equation takes into account light attenuation, lambertian and specular reflection. An image of an object is captured, a virtual light source illuminates the object within the image. In addition, the object can be the head of the user. The position of the head of the user is dynamically tracked so that an three-dimensional model is generated which is representative of the head of the user. Synthetic light is applied to a position on the model to form an illuminated model.

Abstract: A displacement detecting apparatus is provided with a self-position detector for detecting a position and an orientation of the apparatus relative to a preset reference position and a preset reference orientation. Displacement of a rail at an upper surface reference point and a side surface reference point relative to a preset reference position is calculated from imaged image data of the surfaces of the rail using an optical cutting method, and the calculated displacement of the rail is corrected using data obtained from the self-position detector, thereby compensating for errors caused by differences in position and orientation of the apparatus associated with a vehicle running motion. By doing so, the displacement detecting apparatus is superior in maintenance and unlikely to cause measurement errors.

Abstract: A technique for searching for an image includes calculating wavelet features of a plurality of images. A keyword included in radiographic interpretation information is extracted for each of the stored images. The calculated wavelet features and the extracted keywords are stored in association with the respective stored images. A newly taken image is acquired and a wavelet feature of the acquired image is calculated. A keyword included in radiographic interpretation information corresponding to the acquired image is extracted and a search for similar radiographic interpretation information from the stored keywords is performed. A wavelet feature-based spatial distance between the acquired image and each of images corresponding to the radiographic interpretation information found is calculated. A search result of any images for which the calculated wavelet feature-based spatial distance is shorter than a predetermined value is output, in ascending order of the calculated wavelet feature-based spatial distance.

Abstract: A technique for generating a representative image representing a case and radiographic interpretation information for each case includes calculating wavelet features of a plurality of images that have been taken and stored in the past. The calculated wavelet features and extracted keywords are stored in association with the stored images. The stored images are classified on the basis of the extracted keywords to generate a plurality of groups. For each of the generated groups, a centroid vector of wavelet feature-based feature vectors of respective images corresponding to the keywords is calculated and a spatial distance between the calculated centroid vector and each of the wavelet feature-based feature vectors is calculated. For each of the groups, the image for which the calculated spatial distance is the shortest and the radiographic interpretation information associated with the image is stored as a representative image of that group.

Abstract: A method is provided that creates a lecture video capsule containing highlights of an original instructional video based on visual quality and content. The method includes segmenting and recognizing activities in the instructional video using a hidden Markov model (HMM). The activities are classified into three categories: talking head, writing hand and slideshow. The talking head frames are classified as non-content frames, while the writing hand and slideshows are classified as content frames. A non-reference based objective quality assessment of the non-content frames may be performed to detect high quality frames. Statistical parameters of an intensity histogram and a horizontal projection profile (HPP) of the content frames may be used to derive an objective quality measure of the content frames that is used to extract high quality content frames. The selected high quality non-content and content frames form a video clip or capsule, which is a temporally compressed representation of the video.

Abstract: A technique for searching for an image includes calculating wavelet features of a plurality of images. A keyword included in radiographic interpretation information is extracted for each of the stored images. The calculated wavelet features and the extracted keywords are stored in association with the respective stored images. A newly taken image is acquired and a wavelet feature of the acquired image is calculated. A keyword included in radiographic interpretation information corresponding to the acquired image is extracted and a search for similar radiographic interpretation information from the stored keywords is performed. A wavelet feature-based spatial distance between the acquired image and each of images corresponding to the radiographic interpretation information found is calculated. A search result of any images for which the calculated wavelet feature-based spatial distance is shorter than a predetermined value is output, in ascending order of the calculated wavelet feature-based spatial distance.

Abstract: The invention is a method for omnidirectional recognition of recognizable characters in a captured two-dimensional image. An optical reader configured in accordance with the invention searches for pixel groupings in a starburst pattern, and subjects located pixel groupings to a preliminary edge crawling process which records the pixel position of the grouping's edge and records the count of edge pixels. If two similar-sized pixel groupings are located that are of sizes sufficient to potentially represent recognizable characters, then the reader launches “alignment rails” at pixel positions substantially parallel to a centerline connecting the center points of the two similarly sized groupings. A reader according to the invention searches for additional recognizable characters within the rail area, and subjects each located pixel grouping within the rail area to a shape-characterizing edge crawling process for developing data that characterizes the shape of a pixel grouping's edge.

Abstract: Described herein is a method for detecting, identifying and tracking hand, hand parts, and fingers on the hand (500) of a user within depth images of a three-dimensional scene. Arms of a user are detected, identified, segmented from the background of the depth images, and tracked with respect to time. Hands of the user are identified and tracked and the location and orientation of its parts, including the palm and the fingers (510, 520, 530, 540, 550) are determined and tracked in order to produce output information enabling gesture interactions.

Abstract: A two-dimensional code that includes a bar code readable by a scanning operation is provided. The two-dimensional code has an associated alphanumeric representation, and the bar code and the alphanumeric representation represent the same first information. Further, a position of at least one character of the alphanumeric representation with respect to at least one element of the bar code represents second information.

Abstract: Apparatuses, methods and storage medium associated with computing, including processing of image frames, are disclosed herein. In embodiments, an apparatus may include an accelerometer and an image processing engine having an object tracking function. The object tracking function may be arranged to track an object from one image frame to another image frame. The object tracking function may use acceleration data output by the accelerometer to assist in locating the object in an image frame. Other embodiments may be described and claimed.

Abstract: A method of estimating a time to collision (TTC) of a vehicle with an object comprising: acquiring a plurality of images of the object; and determining a TTC from the images that is responsive to a relative velocity and relative acceleration between the vehicle and the object.

Abstract: A method includes checking a specified security feature of a value document which is present in a specified security-feature region of the value document. The security feature includes captured pixel data which describe spatially resolved with a specified optical spatial resolution, an optical image at least of the security-feature region of the value document, and there are captured ultrasound data which describe an ultrasonic property of the value document at least in the security-feature region, spatially resolved with a specified ultrasonic spatial resolution. The ultrasonic spatial resolution is lower than the optical spatial resolution. From the pixel data there are established first reduced-resolution pixel data for reduced-resolution pixels of the first reduced-resolution image which describe a reduced-resolution optical image at least of the security-feature region of the value document, whose optical spatial resolution corresponds to the ultrasonic spatial resolution.

Abstract: Systems and methods are described that provide a fast and simple way of processing meat or food products. Information is compiled and analyzed regarding the condition of a carcass, meat product, styling of the meat product and associated tray or package. Information is used in various processes, including determining which further processing steps are required. The information is also stored for future reference and analysis.