Abstract: An image processing device includes an in-plane pattern detector that selects a pixel of interest in a frame image of interest, calculates in-plane correlation index values representing correlations between the pixel of interest and in-plane pixel patterns including the pixel of interest, and selects a most highly correlated pattern as an in-plane addition pattern. A reference pattern detector calculates inter-plane correlation index values representing correlations between the in-plane pixel addition pattern and reference pixel patterns in a reference frame image temporally adjoining the frame of interest, and selects a most highly correlated reference pixel pattern. A pixel adder adds the values of the pixels in the selected in-plane pixel pattern and the selected reference pixel addition pattern to generate a corrected pixel value, thereby achieving high sensitivity and a high signal-to-noise ratio under low illumination, with little loss of resolution.

Abstract: The invention provides a defect inspection method and a defect inspection device which enable a defect to be inspected regardless of optical conditions. The invention comprises the steps of setting a target local region and a plurality of corresponding local regions in the image signals, the target local region including a target pixel and an area surrounding the target pixel, the corresponding local regions including pixels corresponding to the target pixel and areas surrounding the corresponding pixels; searching similarities between the image signal of the target local region and the image signals of the plurality of corresponding local regions; determining a plurality of image signals that represent corresponding local regions and are similar to the image signal of the target local region; and comparing the image signal of the target local region with the image signals that represent the corresponding local regions.

Abstract: The communications system comprises an encoder for encoding an input image. The salient features of the image prioritized and encoded accordingly. A low bandwidth media for transmitting the encoded input image is used. A decoder is coupled to the encoder for receiving encoded information. The decoder is non-symmetrical to the encoder for decoding merely a part of the encoded input image with improved subjective/perception quality. Whereby a human operator can reach a determination via visual inspection regarding the input image.

Abstract: Techniques are disclosed relating to generating generic labels, translating generic labels to image pipeline-specific labels, and automatically adjusting images. In one embodiment, generic labels may be generated. Generic algorithm parameters may be generated based on training a regression algorithm with the generic labels. The generic labels may be translated to pipeline-specific labels, which may be usable to automatically adjust an image.

Abstract: An information processing system is configured for automated diagnostic analysis of digital images. The system comprises an image classifier operative to receive at least a portion of an image from an image data source and to perform a classification operation on the image based at least in part on information from a knowledge base of one or more previously classified images. The image classifier implements an image processing engine for performing at least a portion of the classification operation. The image processing engine comprises an interconnection of at least one image planner element, a plurality of image scrutinizer elements and at least one image aggregator element. These elements may be selected for use in the image processing engine from a pool of such elements within or otherwise available to the image classifier.

Abstract: An image processing method and an apparatus using the same are provided. The method includes the following steps: deriving a global motion vector between a first image and a second image and providing the first image, the second image and the global motion vector to a first application process, wherein the first image is the previous image of the second image; deriving a first compensated image and a second compensated image by performing a lens distortion compensation process on the first image and the second image respectively; deriving a compensated global motion vector corresponding to the first compensated image and the second compensated image by transforming and correcting the global motion vector; and providing the first compensated image, the second compensated image, and the compensated global motion vector to a second application process.

Abstract: Substantially removing shadows in video images obtained from a camera viewing a scene, at variable pointing angles and magnification, by digital processing of a sequence of frames in the video signal, the processing including—(a) creating and maintaining a model image of the scene, by accumulating image data from a plurality of video frames; (b) in the model image, detecting and defining model shadow zones; (c) calculating correction factors for the model shadow zones; (d) for each frame of the video signal—defining, in the image carried by the signal, shadow zones that correspond to respective model shadow zones; and (e) correcting video signal values in shadow zones accordingly.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing queries made up of images. In one aspect, a method includes indexing images by image descriptors. The method further includes associating descriptive n-grams with the images. In another aspect, a method includes receiving a query, identifying text describing the query, and performing a search according to the text identified for the query.

Abstract: Embodiments for automatic extraction of character ground truth data from images are disclosed. A transcription may be rendered in a plurality of fonts and orientations to obtain a set of candidate word templates with associated character bounding boxes. A word template may be selected from the set of candidate word templates, wherein the selected word template corresponds to a word patch from an image. The character bounding boxes, of the selected word template, may be evaluated in a plurality of orientations about each respective character from the word patch to obtain a set of candidate character templates. For each respective character from the word patch, a character template may be selected from the set of candidate character templates, wherein each selected character template corresponds to the respective character from the word patch.

Abstract: In order to provide a technique for accurately realizing an examination, which is for acquiring a plurality of images of the same examination section, without a complicated operation and an extension of an examination time, body movement information of a subject is acquired immediately before each imaging in an examination, and it is determined whether or not there is a change in the position of the subject by comparing it with body movement information immediately before reference imaging. Only when there is a change in the position of the subject, an imaging slice setting image is acquired again. Then, a recommended imaging slice is calculated using the newest imaging slice setting image.

Abstract: A character recognition apparatus includes an acquisition unit, a specification unit, a movement unit, and a recognition unit. The acquisition unit acquires data representing a character string. The specification unit specifies an element of a compound character satisfying a predetermined condition for determining the compound character from the character string. The movement unit moves the element of the compound character close to an adjacent character. The recognition unit recognizes a changed character string in which the movement unit has moved the element of the compound character, based on a shape of characters and relevance between adjacent characters.

Abstract: Various embodiments of a system and methods for labeling images are described. An image labeling system may receive multiple images. A subset of the images may be labeled to identify image content or elements, such as faces. The system may display some of the labeled image elements in different portions of a display area. Unlabeled image elements may be displayed in the same display area. The display size and position of each unlabeled image element may be dependent on similarities between the unlabeled image element and the displayed, labeled image elements. The system may receive input which indicates that one or more of the displayed, unlabeled image elements should receive the same label as one of the displayed, labeled image elements. Similarities between image elements may be re-analyzed, dependent on the assigned labels, and the display of unlabeled images may be updated.

Abstract: Objects in an image are classified by applying an appearance classifier to the image to determine candidates of the objects and statistics associated with the candidates, wherein the appearance classifier uses a set of windows, and the candidates are in selected windows. Then, a context classifier is applied only to the selected windows of the image to determine an identity, and location of objects in the image.

Abstract: A method for feature matching in image recognition is provided. First, image scaling may be based on a feature distribution across scale spaces for an image to estimate image size/resolution, where peak(s) in the keypoint distribution at different scales is used to track a dominant image scale and roughly track object sizes. Second, instead of using all detected features in an image for feature matching, keypoints may be pruned based on cluster density and/or the scale level in which the keypoints are detected. Keypoints falling within high-density clusters may be preferred over features falling within lower density clusters for purposes of feature matching. Third, inlier-to-outlier keypoint ratios are increased by spatially constraining keypoints into clusters in order to reduce or avoid geometric consistency checking for the image.

Abstract: Methods are provided for generating a low dimension pose space and using the pose space to estimate one or more head rotation angles of a user head. In one example, training image frames including a test subject head are captured under a plurality of conditions. For each frame an actual head rotation angle about a rotation axis is recorded. In each frame a face image is detected and converted to an LBP feature vector. Using principal component analysis a PCA feature vector is generated. Pose classes related to rotation angles about a rotation axis are defined. The PCA feature vectors are grouped into a pose class that corresponds to the actual rotation angle associated with the PCA feature vector. Linear discriminant analysis is applied to the pose classes to generate the low dimension pose space.

Abstract: An image processing system includes a difference detecting module for determining whether second image data is identical to first image data to generate a determination result, and an image processing module for processing the first image data to generate a first image processed result and selectively processing the second image data. The image processing module includes a data path and a control path. According to a reference clock signal, the first and second image data are transmitted via the data path, and the determination result is transmitted via the control path. When the determination result is affirmative, the reference clock signal provided to the data path is gated, so that, without processing the second image data, the image processing module outputs the first image processed result as a second image output corresponding to the second image data.

Abstract: A method for correcting a relaxation map of an object scanned with a magnetic resonance imaging modality the object having a plurality of structure and/or tissue types. The method includes deriving a first relaxation map of a scanned object from at least two three-dimensional scans of the object acquired using a sequence of ultrashort echo time pulses adapted for distinguishing between the various types of a plurality of structure and/or tissue types of the object. Information is obtained on the type of structure and/or tissue type present in voxels in the first relaxation map and binarizing the obtained information. A corrected relaxation map is generated by combining the binarized information with the first relaxation map.

Abstract: In an embodiment, a method is provided. The method includes setting an IR (infrared) level to a first predetermined level. The method also includes reading an image and determining if a face is detected. If a face is not detected, the method sets the IR level to zero and waits a first predetermined amount of time. The method further includes repeating the setting the IR level to the first predetermined level and the reading an image. The method also includes determining a face is detected. The method further includes setting the IR level to a second predetermined level. The method also includes reading an image and determining if a face is recognized. The method may further include setting the IR level to zero and waiting a second predetermined amount of time. The method may also include setting the IR level to the first predetermined level, reading an image and determining if a face is detected.

Abstract: An image processing apparatus includes a face detector for detecting a face region from an image including a face of a user, a part detector for detecting a positional layout of a part of the face included in the face region detected by the face detector, a determiner for determining an attribute of the face on the basis of the positional layout of the part detected by the part detector and calculating a score indicating attribute determination results, a model selector for selecting, on the basis of the score calculated by the determiner, a model that is to be displayed in place of the face of the user in the image, and an image generator for generating an image of a face of the model selected by the model selector and synthesizing the image of the face of the model with the face of the user within the face region.

Abstract: The present technology relates to an image processing device including: a reducing section configured to generate a plurality of reduced images by reducing an input image at a plurality of reduction ratios; a noise removal processing section configured to generate noise-removed images by performing noise removal processing on each of the reduced images; an enlarging section configured to generate enlarged images equal to each other in size by enlarging each of the noise-removed images; and a mixing section configured to generate an output image by mixing two or more different enlarged images of the enlarged images with each other.