Abstract: A driving assistant method applied to a first moving vehicle is provided. The method includes capturing an image of a license plate of a second moving vehicle when the first moving vehicle is moving, and identifying a first area of the license plate in the captured image. Basic information of the second moving vehicle are obtained according to a size of the first area. Once a safe distance is determined according to driving information of the first moving vehicle and the basic information of the second moving vehicle, a warning message is transmitted when the distance between the first moving vehicle and the second moving vehicle is less than the safe distance.

Abstract: Location-based binning can separate defects on different rows of channel holes in a 3D NAND structure to corresponding bins. A one-dimensional projection of an image is generated and a one-dimensional curve is formed. A mask is generated from the one-dimensional curve. Defects in the image are detected using the mask and location-based binning is performed.

Abstract: Provided are an image processing device, an image processing method, and an image processing program that can decide a user image that is similar to a plurality of model images and that follows a flow of the plurality of model images. Combinations of (I2) and (P3), (I51) and (P21), (I150) and (P49), (I198) and (P79), (I201) and (P30), (I249) and (P99), (I300) and (P101), and (I301) and (P112) in which similarities between the model images and the user images are equal to or more than a first threshold value are detected. The combination of (I201) and (P30) in which a relative time difference of the imaging time is equal to or more than a second threshold value is eliminated, and the rest combinations are second combinations. From among the second combinations, a model image group and a user image group, which are a collection of similar images, are decided, and the user images similar to the model images attached on a model album are decided from the user image group.

Abstract: An image presentation method includes obtaining a first image and a second image having same contents; size-processing the first image according to at least one of a target resolution, an aspect ratio of the first image, or an aspect ratio of the second image to generate a size-processed first image having the target resolution; generating a presenting image at least by combining the size-processed first image and the second image; and encoding the presenting image in a code stream and transmitting the encoded image to the display device that requires the preset resolution for display. The first and second images include a visible-light image and an infrared image. The presenting image has a preset resolution no less than a sum of the target resolution and a resolution of the second image. The size-processed first image and the second image are arranged in the presenting image without partially blocking each other.

Abstract: A method includes receiving a first depth map that includes a plurality of first pixel depths and a second depth map that includes a plurality of second pixel depths. The first depth map corresponds to a reference depth scale and the second depth map corresponds to a relative depth scale. The method includes aligning the second pixel depths with the first pixel depths. The method includes transforming the aligned region of the second pixel depths such that transformed second edge pixel depths of the aligned region are coextensive with first edge pixel depths surrounding the corresponding region of the first pixel depths. The method includes generating a third depth map. The third depth map includes a first region corresponding to the first pixel depths and a second region corresponding to the transformed and aligned region of the second pixel depths.

Abstract: Examples for determining a confidence level associated with image segmentation are disclosed. A confidence level associated with a collective image segmentation result can be determined by generating multiple individual segmentation results each from the same image data. These examples can then aggregate the individual segmentation results to form the collective image segmentation result and measure the spread of each individual segmentation result from the collective image segmentation result. The measured spread of each individual segmentation result can then be used to determine the confidence level associated with the collective image segmentation result. This can allow a confidence level associated with the collective image segmentation result to be determined. This confidence level may be determined without needing a ground truth to compare to the collective image segmentation result.

Abstract: In one embodiment, a set of feature vectors can be derived from any biometric data, and then using a deep neural network (“DNN”) on those one-way homomorphic encryptions (i.e., each biometrics' feature vector) an authentication system can determine matches or execute searches on encrypted data. Each biometrics' feature vector can then be stored and/or used in conjunction with respective classifications, for use in subsequent comparisons without fear of compromising the original biometric data. In various embodiments, the original biometric data is discarded responsive to generating the encrypted values. In another embodiment, the homomorphic encryption enables computations and comparisons on cypher text without decryption of the encrypted feature vectors. Security of such privacy enable biometrics can be increased by implementing an assurance factor (e.g., liveness) to establish a submitted biometric has not been spoofed or faked.

Abstract: A method for template matching can include iteratively selecting a template set of points to project over a centerline of a candidate symbol; conducting a template matching analysis; assigning a score to each template set; and selecting a template set with a highest assigned score. For example, the score can depend on proximity of the template points to a center and/or boundaries of a principal tracing path of the symbol. Additionally, one or more template sets having a top rank can be selected for a secondary analysis of proximity of the template points to a boundary of a printing of the symbol. The method can further include using the template with the highest score to interpret the candidate symbol.

Abstract: A hyperspectral imaging spectrophotometer and system, with calibration, data collection, and image processing methods designed to match human visual perception and color matching of complex colored objects.

Abstract: Systems and methods for eye pose identification using features of an eye are described. Embodiments of the systems and methods can include segmenting an iris of an eye in the eye image to obtain pupillary and limbic boundaries of the eye, determining two angular coordinates (e.g., pitch and yaw) of an eye pose using the pupillary and limbic boundaries of the eye, identifying an eye feature of the eye (e.g., an iris feature or a scleral feature), determining a third angular coordinate (e.g., roll) of the eye pose using the identified eye feature, and utilizing the eye pose measurement for display of an image or a biometric application. In some implementations, iris segmentation may not be performed, and the two angular coordinates are determined from eye features.

Abstract: An energy optimized imaging system that includes a light source that has the ability to illuminate specific pixels in a scene, and a sensor that has the ability to capture light with specific pixels of its sensor matrix, temporally synchronized such that the sensor captures light only when the light source is illuminating pixels in the scene.

Abstract: Methods and systems for setting up alignment of a specimen are provided. One system includes computer subsystem(s) configured for acquiring two-dimensional (2D) images generated from output of a detector of an output acquisition subsystem at template locations in corresponding areas of printed instances on a specimen. The computer subsystem(s) determine offsets in x and y directions between the template locations using the 2D images and determine an angle of the specimen with respect to the output acquisition subsystem based on the offsets. If the angle is greater than a predetermined value, the computer subsystem(s) rotate the specimen and repeat the steps described above. If the angle is less than the predetermined value, the computer subsystem(s) store one of the 2D images for alignment of the specimen in a process performed on a specimen. The 2D images may include multi-mode images, which may be fused prior to determining the offsets.

Abstract: Techniques are disclosed for text-conditioned image searching. A methodology implementing the techniques includes decomposing a source image into visual feature vectors associated with different levels of granularity. The method also includes decomposing a text query (defining a target image attribute) into feature vectors associated with different levels of granularity including a global text feature vector. The method further includes generating image-text embeddings based on the visual feature vectors and the text feature vectors to encode information from visual and textual features. The method further includes composing a visio-linguistic representation based on a hierarchical aggregation of the image-text embeddings to encode visual and textual information at multiple levels of granularity.

Abstract: The invention provides a method for controlling the generation of a compound ultrasonic image. The method includes obtaining a first ultrasound image and applying adaptive beamforming to the first ultrasound image, thereby generating a second ultrasound image. A weighting is determined based on the first and second ultrasound images, wherein the weighting comprises at least one weighting component. The compound ultrasound image is then generated based on the first and second ultrasound images and the weighting component.

Abstract: A method of generating a 3D reconstruction of a scene, the scene comprising a plurality of cameras positioned around the scene, comprises: obtaining the extrinsics and intrinsics of a virtual camera within a scene; accessing a data structure so as to determine a camera pair that is to be used in reconstructing the scene from the viewpoint of the virtual camera; wherein the data structure defines a voxel representation of the scene, the voxel representation comprising a plurality of voxels, at least some of the voxel surfaces being associated with respective camera pair identifiers; wherein each camera pair identifier associated with a respective voxel surface corresponds to a camera pair that has been identified as being suitable for obtaining depth data for the part of the scene within that voxel and for which the averaged pose of the camera pair is oriented towards the voxel surface; identifying, based on the obtained extrinsics and intrinsics of the virtual camera, at least one voxel that is within the fie

Abstract: Implementations relate to detecting/replacing transient obstructions from high-elevation digital images. A digital image of a geographic area includes pixels that align spatially with respective geographic units of the geographic area. Analysis of the digital image may uncover obscured pixel(s) that align spatially with geographic unit(s) of the geographic area that are obscured by transient obstruction(s). Domain fingerprint(s) of the obscured geographic unit(s) may be determined across pixels of a corpus of digital images that align spatially with the one or more obscured geographic units. Unobscured pixel(s) of the same/different digital image may be identified that align spatially with unobscured geographic unit(s) of the geographic area. The unobscured geographic unit(s) also may have domain fingerprint(s) that match the domain fingerprint(s) of the obscured geographic unit(s).

Abstract: A stress luminescence measurement method according to one aspect includes the steps of: placing a stress luminescent material on a surface of a sample; irradiating the stress luminescent material with excitation light; acquiring a first captured image by imaging the stress luminescent material during irradiation of the excitation light; applying a load to the sample; acquiring a stress luminescence image by imaging stress luminescence of the stress luminescent material; irradiating the stress luminescent material after removal of the load with the excitation light; acquiring a second captured image during irradiation of the excitation light by imaging the stress luminescent material in a state in which the load has been removed; and storing the first captured image and the second captured image in a memory in association with the stress luminescent image.

Abstract: A book made up of pages is described. At least some of the pages contain both space for manually-created visual content, and instances of preprinted indexing target symbols. Each of the indexing target symbol instances has at least a portion within one inch of three unbound page edges. When the book is closed, the instances of each particular indexing target symbol are in a substantially collinear stack that is substantially perpendicular to the faces of the pages.

Abstract: An inspection method is provided for checking the integrity of a combination of a security marking and an identification label, the security marking including at least one contrast field having a comparatively high reflectivity in a first and a second wavelength range, and a security field, having different reflection properties in the first wavelength range compared to the second wavelength range, and the identification label having at least one light background around mark components printed with dark color. The inspection method may include capturing possibly averaged gray values of the contrast field and the identification label background, comparing the gray values, and determining whether the gray value of the contrast field of the security marking deviates from the gray value of the background of the identification label by less than a predefined maximum amount.

Abstract: A CNN operates on the disparity or motion outputs of a block matching hardware module, such as a DMPAC module, to produce refined disparity or motion streams which improve operations in images having ambiguous regions. As the block matching hardware module provides most of the processing, the CNN can be small and thus able to operate in real time, in contrast to CNNs which are performing all of the processing. In one example, the CNN operation is performed only if the block hardware module output confidence level is below a predetermined amount. The CNN can have a number of different configurations and still be sufficiently small to operate in real time on conventional platforms.