Abstract: A method of locating content portion(s) of an image includes automatically determining a pixel threshold value; comparing the threshold value to the image to determine background and content sets of the pixels; determining boundaries between the background and content sets; determining the content portions using the determined boundaries; and determining bounding boxes for the content portions. A computed-radiography scanner includes an imager; a transport configured to operatively arrange a plurality of plates with respect to the imager so that a single image of the plates can be captured; and a processor configured to automatically locate the content portion(s) in the single image. A locating method includes automatically determining the pixel threshold value; determining the boundaries between portions delimited by the pixel threshold value; determining the content portions using the boundaries; and determining the bounding boxes.

Abstract: Provided is a method for generating a 3D point cloud and colour visualisation of an underwater scene, the point cloud comprising a set of (x, y, z) coordinates relating to points in the scene, the method operating in a system comprising at least one camera module, at least one structured light source, and a processing module, each of the at least one camera module being directed at the scene and having substantially the same overlapped field of view.

Abstract: A processing device receives input representing a selection of a first area of a source image. The processing device sends a request to a server machine for a result image that corresponds to the source image. The processing device, responsive to determining that the server machine does not have the result image, creates a blurred area for the first area, the blurred area corresponding to a portion of the image that contains the first area. The portion of the image having a size that is greater than an aggregate size of the first area and less than the size of the image. The processing device also sends the blurred area to the server machine for storage of the blurred area as the result image. The processing device replaces the first area with the corresponding portion of the blurred area without blurring a remaining area of the image.

Abstract: Provided is an image processing device that can suppress deterioration in the accuracy of identifying a subject, even in cases where the shape of the subject in an image is deformed. A feature amount calculation means 81 detects feature points from an image, and calculates, for each feature point, a local feature amount for the feature point on the basis of a peripheral region of said feature point, including said feature point. A correlation identifying means 82 specifies the correlation between feature points in a first image and feature points in a second image on the basis of the local feature amount of each feature point in the first image and the local feature amount of each feature point in the second image. A partial region detection means 83 detects, from one of the first image or the second image, partial regions each including a feature point in said image.

Abstract: Embodiments of the present invention analyze and score each image associated with a group to determine representative image or images for the group. Such analysis can include detecting objects shown in the images, determining the quality of the images, and/or contextually analyzing the images as a group. In some embodiments, each image in a group (e.g., an event) of images can be analyzed by one or more image analysis modules that calculate a score for the image based on a different image characteristic. A composite image score can then be calculated based on the various image characteristic scores to identify the image or images to be used as to represent the group.

Abstract: A method of performing character isolation in an optical character recognition process, the method comprising receiving image data representing one or more character columns, determining a number of black pixels in each column of the image data, defining a vertical separation threshold which is a maximum number of black pixels in a column, dividing the columns into different pixel groups and groups of excluded columns by excluding any columns with a number of black pixels below the vertical separation threshold, identifying the pixel group representing the left most character column in the image data, determining whether there are one or two pixel groups representing character columns in the image data and, if it is determined that there are two pixel groups representing character columns, using a predetermined width value for a right most character column in order to identify a right hand boundary of the right most character column.

Abstract: Systems and methods for detecting cracks in an electronic device are disclosed. In one embodiment, the method includes receiving an image of a front side of a mobile device and automatically identifying edges in the image. For given edges among the identified edges, the method includes determining whether another edge among the identified edges is present within a predetermined distance of the given edge. Next, straight line segments corresponding to the edges for which another edge is within the predetermined distance are identified, and then a crack evaluation assessment is assigned to the mobile device based at least in part on the identified straight line segments.

Abstract: Provided is an image processing apparatus and method that may employ a new program or protocol without having to additionally develop a new program or a protocol for image processing. The image processing apparatus may include: an open platform-compatible unit configured to determine a protocol that is used by a video analysis application installed in or connected to the image processing apparatus, and receive at least one of channel information about an original image, channel information about an encoded image, channel information about a decoded image, resolution information about the decoded image and frame rate information that is required to receive the decoded image, in accordance with the determined protocol; and a protocol conversion unit configured to process an input image to comply with the determined protocol, based on the at least one information that is received at the open platform-compatible unit.

Abstract: A method includes identifying, by a processor, a gauge dial pattern in a first file based on a gauge dial template in a second file; identifying, by the processor, a needle pattern in the first file; generating, by the processor, a line pattern that approximates the needle pattern; determining, by the processor, a deflection angle of the needle pattern with respect to the gauge dial pattern based on the line pattern; converting, by the processor, the deflection angle into a reading of the gauge dial pattern based on the gauge dial template; and taking, by the processor, an action based on the reading.

Abstract: It is inter alia disclosed to classify samples of a set of samples of an image regarding whether or not a respective sample comprises optical information on a specific object type based on classification information. Therein, the classification information comprises a plurality of classifiers, each classifier being associated exclusively with one color channel of a plurality of color channels.

Abstract: A processing device includes: a memory that stores first difference information representing a difference between a judgment use frame in reference information and a representative frame in association with the reference information; and a judging unit that, based on second difference information representing a difference between a judgment frame in input information and the representative frame and on the first difference information stored in the memory, judges the input information by use of the reference information.

Abstract: The disclosure provides an approach for denoising (also referred to as “filtering”) rendered images. In one embodiment, a denoising application takes as input rendered images and feature buffers that encode image information such as surface positions, surface depths, surface normals, surface albedos, and distances to the camera. For each pixel in a received image, the denoising application performs a first-order regression in a predefined neighborhood of the pixel to find a linear combination of pixel features that fits pixel colors in the predefined neighborhood. In such a first-order regression, the local regression weight of each pixel in the neighborhood may be determined using a metric which computes distances based on color values in patches around pixels being compared. In another embodiment, collaborative filtering may be performed in which filtered output from the first-order regression in each neighborhood is averaged with filtered output from overlapping neighborhoods to obtain a final output.

Abstract: In one embodiment, a method includes accessing an original image of a person's face to be smoothed. A second image may be generated to include color information corresponding to those of the original image. The color information of the second image may be blurred. A filter image may be generated and may include an Alpha channel and color channels. The Alpha channel may include a mask representing opaque and transparent information, and the color channels may include a smoothed original image. High frequency color information may be determined from the color information of the original image and used to modify the color information of the filter image. A display may be outputted based on an overlay of the modified filter image over the original image.

Abstract: Implementations generally relate to data-charge phase data compression. In one implementation, a method includes computing prediction values for image data, where the image data is data-charge phase data, and where the computing of prediction values is based on inter-block prediction. The method also includes computing residual data based on the prediction values. The method also includes quantizing the residual data. The method also includes entropy encoding the quantized residual data. The method also includes refining an inverse quantized residual data based on one or more of the residual data and a number of left-over bit-budget after entropy encoding.

Abstract: Systems and methods for eyelid shape estimation are disclosed. In one aspect, after receiving an eye image of an eye (e.g., from an image capture device), an eye-box is generated over an iris of the eye in the eye image. A plurality of radial lines can be generated from approximately the center of the eye-box to an upper edge or a lower edge of the eye box. Candidate points can be determined to have local maximum derivatives along the plurality of radial lines. From the candidate points, an eyelid shape curve (e.g., for an upper eyelid or a lower eyelid) can be determined by fitting a curve (e.g., a parabola or a polynomial) to the candidate points or a subset of the candidate points.

Abstract: A display device, including a content receiving unit configured to receive a high dynamic range image, an image processing unit configured to detect a first region whose luminance value is equal to or greater than a reference luminance value within the high dynamic range image and perform tone mapping on an image of the first region based on feature information of the image of the first region, and a display unit configured to display a low dynamic range image on which the tone mapping is performed.

Abstract: Approaches attempt to determine information that can help to produce more useful recommendations to be displayed in a situation where no, or little, information is available that indicates a relationship between content provided through an electronic marketplace or other content provider. For example, data available that relates to an item in a product catalog, for example color data, can be analyzed and aggregated in order to attempt to locate other items that are related and relevant to the item, at least as it relates to color and categorization of the content. Such approaches can include, for example, analyzing images, articles, and other sources of electronic content to attempt to locate items that might be relevant to the item of interest.

Abstract: A method and apparatus for whole body bone removal and vasculature visualization in medical image data, such as computed tomography angiography (CTA) scans, is disclosed. Bone structures are segmented in the a 3D medical image, resulting in a bone mask of the 3D medical image. Vessel structures are segmented in the 3D medical image, resulting in a vessel mask of the 3D medical image. The bone mask and the vessel mask are refined by fusing information from the bone mask and the vessel mask. Bone voxels are removed from the 3D medical image using the refined bone mask, in order to generate a visualization of the vessel structures in the 3D medical image.

Abstract: An image composition device composites a no-flash image including a subject captured under ambient light and a flash image including the subject captured by emitting flash light to generate a composite image including the subject. The image composition device includes an input unit that enables the no-flash image and the flash image to be input, a correction unit that corrects the no-flash image and the flash image input from the input unit, and a composition unit that composites the no-flash image and the flash image output from the correction unit to generate a composite image. The correction unit corrects a color temperature of the no-flash image.

Abstract: Technologies for multi-channel feature detection include a computing device to determine a filter response of each image channel of a multi-channel image for one or more image filters. The computing device determines a local differentiating color vector based on the filter responses, applies the filter responses to the local differentiating color vector to generate an adapted response, and determines a total response of the multi-channel image based on the adapted response.