Abstract: A method of filtering video packets for video stream monitoring is provided. A video packet of a video stream is received. One or more features are extracted from a specified frame of the video packet via one or more histograms and frequency domain coefficients of the specified frame. One or more concept detectors are implemented on the one or more features creating one or more confidence values. The confidence values are transmitted to a display module for filtering of video packets.

Abstract: This present invention provides an image processing system and image processing method which can reliably transmit image information to a destination without attaching a large file which applies load to an e-mail system or reception terminal and make the receiving side easily acquire necessary image data on the basis of determination on the receiving side. In an image input/output device (10), image information is input from an image input device (201) and stored in a HDD (208) in a control unit (200). A low-resolution image or vector data is generated from the image information in accordance with the properties of objects contained in the image information. The generated information and information about the storage location of the image information are transmitted to a designated transmission destination.

Abstract: The usability of an electronic device that includes an integrated fingerprint sensor is enhanced by mounting the fingerprint sensor rotatably and pivotably. The fingerprint sensor is prevented from moving during normal use, but the fingerprint sensor may be repositioned to accommodate a user's preferences.

Abstract: A technique for estimating the optical flow between images of a scene and a segmentation of the images is presented. This involves first establishing an initial segmentation of the images and an initial optical flow estimate for each segment of each images and its neighboring image or images. A refined optical flow estimate is computed for each segment of each image from the initial segmentation of that image and the initial optical flow of the segments of that image. Next, the segmentation of each image is refined from the last-computed optical flow estimates for each segment of the image. This process can continue in an iterative manner by further refining the optical flow estimates for the images using their respective last-computed segmentation, followed by further refining the segmentation of each image using their respective last-computed optical flow estimates, until a prescribed number of iterations have been completed.

Abstract: A method for classifying features in a digital medical image includes providing a plurality of feature points in an N-dimensional space, wherein each feature point is a member of one of two sets, determining a classifying plane that separates feature points in a first of the two sets from feature points in a second of the two sets, transforming the classifying plane wherein a normal vector to said transformed classifying plane has positive coefficients and a feature domain for one or more feature points of one set is a unit hypercube in a transformed space having n axes, obtaining an upper bound along each of the n-axes of the unit hypercube, inversely transforming said upper bound to obtain a new rule containing one or more feature points of said one set, and removing the feature points contained by said new rule from said one set.

Abstract: An image-capturing device and method for removing strangers from an image are described. First, a first image is input. Then, a control module determines if an unwanted object processing step is needed, and obtains a result. If the result is no, the first image is directly sent to an output module. If the result is yes, an image-identifying module begins to identify the target-image and the unwanted object in the first image, and then, an unwanted object processing module starts the step to process unwanted images. The unwanted object processing step can remove the unwanted object from an image and fill the left lacuna region. Afterwards, a second image is produced and sent to the output module.

Abstract: A method for identifying a projection view and an orientation of a chest radiograph. The method includes the steps of: providing an input digital image of the chest radiograph; preprocessing the input digital radiographic image; classifying the view of the input digital radiographic image; and determining the orientation of the input digital radiographic image.

Abstract: An aspect of the present invention provides a moving obstacle detecting device installed in or on a moving body for detecting moving obstacles in the vicinity of the moving body, the moving obstacle detecting device that includes an image capturing unit configured and arranged to capture an image of the surroundings of the moving body, an optical flow calculating unit configured to find an optical flow corresponding to characteristic points in the image captured with the camera, a focus of expansion calculating unit configured to calculate focus or foci of expansion of the motion vectors in the optical flow found by the optical flow calculating unit, a histogram creating unit configured to create a histogram of the distribution of the focus or foci of expansion calculated by the focus of expansion calculating unit, a peak test unit configured to detect at least one moving obstacle to test peaks in the histogram, the test determining whether or not the peaks correspond to the same object if two or more peaks e