Abstract: The method and system may be used to provide an indication of a color value for a particular siding sample and to color match a specific siding product to the color value of the siding sample. The system receives a digital image of a siding sample and a desired color value to be matched. A color query module plots this desired color value as a desired color point in a multidimensional color space together with a plurality of color reference points. Each color reference point represents the color value of an existing siding product. The system determines a “distance” between the desired color point and each plotted color reference point within the color space and identifies the siding product associated with the color reference point that is located the shortest distance to the desired color point within the color space.

Abstract: An ophthalmic image processing apparatus that processes pieces of image data of a subject eye which are acquired by a plurality of ophthalmic examination apparatuses including a first ophthalmic examination apparatus obtaining first image data of the subject eye and a second ophthalmic examination apparatus obtaining second image data of the subject eye includes: a processor; and memory storing computer readable instructions, when executed by the processor, causing the ophthalmic image processing apparatus to execute: setting process of setting image types for the first image data and the second image data that form a registration image; and image processing process of generating the registration image in which the first image data and the second image data which correspond to the image types set in the setting process are superimposed on each other, and outputting the generated registration image.

Abstract: Various embodiments of present invention provide systems, methods, and computer-program products containing executable code for processing a package for shipping with a common carrier. Various embodiments include a wireless computing device that may be one of several types of devices such as smartphones, mobile telephones, mobile computers, portable digital assistants, laptop computers, gaming devices, electronic tablets, or other types of similar devices. In particular embodiments, executable code is installed on the wireless computing device that, when executed, causes the device to perform certain functionality. For instance, in particular embodiments, the wireless computing device records an image of a shipping form being placed on a package, verifies the image is suitable for analysis and transmission, and extracts a tracking number from the image.

Abstract: A system according to the present disclosure includes an edge detection module, a hitch identification module, a guidance line module, and a display control module. The edge detection module detects edges of an object within an image of a cargo bed of a vehicle. The hitch identification module identifies at least one of a type of a trailer hitch attached to the cargo bed and a size of the trailer hitch based on the detected edges of the object. The guidance line module determines a starting point of a guidance line for connecting a trailer to the trailer hitch based on at least one of the type of the trailer hitch and the size of the trailer hitch. The display control module controls an electronic display to display the image of the cargo bed and to display the guidance line on the image of the cargo bed.

Abstract: The present application provides an eyeglass positioning method. The method includes: acquiring a real-time image shot by a shooting apparatus, and extracting a real-time face image from the real-time image using a face recognition algorithm; recognizing whether the real-time face image includes eyeglasses using a predetermined first classifier, and outputting a recognition result; and positioning the eyeglasses in the real-time face image using a predetermined second classifier and outputting a positioning result when the recognition result is that the real-time face image includes the eyeglasses. The present application also provides an electronic apparatus and a computer readable storage medium. The present application adopts two classifiers to detect images in eyeglass regions in the face images, thereby enhancing precision and accuracy of eyeglass detection.

Abstract: Aspects determining anomalous events, wherein processors determine a trajectory of tracked movement of an object through an image field of a camera partitioned into a matrix grid of different local units. The aspects generate anomaly confidence decision values for image features extracted from video data of the tracked movement of the object as a function of fitting extracted image features to normal patterns of local motion pattern models defined by dominant distributions of extracted image features. The aspects further extract trajectory features from the video data relative to the trajectory of the tracked movement of the object, and generate global anomaly confidence decision values for the object trajectory as a function of fitting the extracted trajectory features to a normal learned motion trajectory model. The aspects determine anomalous events as a function of the generated global anomaly confidence decision value and the anomaly confidence decision values.

Abstract: A pointing vector is determined for a gesture that is performed before a depth camera. One example includes receiving a first and a second image of a pointing gesture in a depth camera, the depth camera having a first and a second image sensor, applying erosion and dilation to the first image using a 2D convolution filter to isolate the gesture from other objects, finding the imaged gesture in the filtered first image of the camera, finding a pointing tip of the imaged gesture, determining a position of the pointing tip of the imaged gesture using the second image, and determining a pointing vector using the determined position of the pointing tip.

Abstract: A method for detecting fingerprint spoof objects includes detecting a presence of the object at a fingerprint sensor and, in response to detecting the presence of the object, measuring a set of physical properties of the object based on one or more signals from a set of electrodes of the fingerprint sensor. The set of physical properties includes at least one of a subdermal compliance of the object and a surface adhesiveness of the object. The method further includes distinguishing the object as an actual finger or a spoof based on the one or more physical properties.

Abstract: Techniques describe submitting a video clip as a query by a user. A process retrieves images and information associated with the images in response to the query. The process decomposes the video clip into a sequence of frames to extract the features in a frame and to quantize the extracted features into descriptive words. The process further tracks the extracted features as points in the frame, a first set of points to correspond to a second set of points in consecutive frames to construct a sequence of points. Then the process identifies the points that satisfy criteria of being stable points and being centrally located in the frame to represent the video clip as a bag of descriptive words for searching for images and information related to the video clip.

Abstract: Disclosed herein are system, method, and computer program product embodiments for locating, identifying, and tracking a known criminal, fugitive, missing person, and/or any other person of interest. An embodiment operates by deploying an unmanned aerial vehicle, determining the mode of operation of the UAV, operating the UAV in accordance with the mode of operation of the UAV, determining whether a subject has been detected, capturing a first voice sample associated with the subject, authenticating the identity of the subject, and transmitting the GPS location of the unmanned aerial vehicle to a computing device.

Abstract: Apparatus and methods to unwarp at least portions of distorted, electronically-captured images are described. Keypoints, instead of an entire image, may be unwarped and used in various machine-vision algorithms, such as object recognition, image matching, and 3D reconstruction algorithms. When using unwarped keypoints, the machine-vision algorithms may perform reliably irrespective of distortions that may be introduced by one or more image capture systems.

Abstract: A method for detecting objects in the surroundings of a vehicle. The method includes reading in a first image, of a vehicle camera, which represents the surroundings taken using a first exposure time and reading in a second image of the vehicle camera, which was taken after the first image and using a second exposure time, the second exposure time differing from the first exposure time, and extracting an image detail from the second image, the image detail representing a smaller area of the surroundings than the first image. During the extracting, a position of the image detail in the second image is determined based on at least one parameter which represents information on travel of the vehicle and/or a position of an infrastructure measure in front of the vehicle and/or which is independent of a moving object that was detected in a preceding step in the image detail.

Abstract: A computer, which is configured to extract an attribute being a character string indicating a feature of a paper-based document, the computer stores template information dictionary information. The computer is configured to: execute character recognition processing on image data on the paper-based document; extract an attribute corresponding to each of the at least one type of attribute, which is defined in each of the plurality of templates, through use of a result of the character recognition processing and the plurality of templates; calculate a score regarding the extracted attribute for each of the plurality of templates; select one of the plurality of templates that has the highest extraction accuracy of the attribute based on the score; and generate output information through use of the selected template.

Abstract: A method includes combining a plurality of different types of spectral images into a first single blended image based on a first blend point of a first spectral image data blend map. The first blend point includes a first set of weight values. The first set of weight values includes a weight value for each of the plurality of different types of spectral images. The plurality of different types of spectral images is combined based on the first set of weight values. The method further comprising displaying the first single blended image via a display device.

Abstract: A position detection apparatus (100) which detects a position of an object includes a scale (2) including a periodic pattern, a detector (7) configured to be movable relative to the scale, and a signal processor (101) configured to acquire position information of the object based on a first output signal from the detector and perform abnormality determination based on a second output signal from the detector, a spatial frequency response of the first output signal is peaked at a first spatial frequency, and a spatial frequency response of the second output signal is peaked at a second spatial frequency different from the first spatial frequency.

Abstract: A region identifier identifies a region within a diagnostic image corresponding to one of plural predetermined clinical findings according to a first feature value from a feature value detector. A level detector performs level detection of the region at one of plural levels associated with the clinical findings for evaluation of the clinical findings according to a second feature value from a feature value detector. A color mapped image generator generates a color mapped image by color mapping of the diagnostic image with a display color associated with respectively the clinical findings and chromaticity of the display color associated with the levels. A monitor display panel is caused to display the color mapped image by control of a display control unit. Preferably, the diagnostic image is an image generated by an endoscope. The color mapped image generator is included in a processing apparatus.

Abstract: Methods to create montages of wide-field fundus images, while correcting for the projective distortion inherent to an imaging system are described. The methods use specific knowledge of the imaging geometry of the particular imaging system to map the fundus images onto a set of 3D ray vectors, which allows them to be stitched together efficiently and precisely. After co-aligning the images using feature detection and matching, the registered images are projected back into 2D to generate the final montaged image. The method could be used on any type of wide-field fundus images including, but not limited to, those generated from optical coherence tomography, optical coherence tomography angiography, and broad-line fundus imaging systems.

Abstract: An imaging system includes an imaging unit, a display unit, and at least one processor. The at least one processor is configured to acquire a first type of diagnostic imaging information of the patient; reconstruct a first image using the first type of diagnostic imaging information; if a first stop criterion for terminating imaging is not satisfied, acquire a second type of diagnostic imaging information having an increased level of acquisitional burden; reconstruct a second image; if a second stop criterion for terminating imaging is not satisfied, acquire a third type of diagnostic imaging information having an increased level of acquisitional burden, wherein the patient is maintained on a table of the imaging unit during the acquisition of the second type of diagnostic imaging information, reconstruction of the second image, and acquisition of the third type of diagnostic imaging information; reconstruct a third image; and display the third image.

Abstract: Both pixel-oriented analysis and the more accurate yet slower object-oriented analysis are used to recognize patterns in images of stained cancer tissue. Images of tissue from other patients that are similar to tissue of a target patient are identified using the standard deviation of color in the images. Object-oriented segmentation is then used to segment small portions of the images of the other patients into object exhibiting object characteristics. Pixelwise descriptors associate each pixel in the remainder of the images with object characteristics based on the color of pixels at predetermined offsets from the characterized pixel. Pixels in the image of the target patient are assigned object characteristics without performing the slow segmentation of the image into objects. A pixel heat map is generated from the target image by assigning pixels the color corresponding to the object characteristic that the pixelwise descriptors indicate is most likely associated with each pixel.

Abstract: In implementations of the subject matter described herein, a solution for object detection is proposed. First, a feature(s) is extracted from an image and used to identify a candidate object region in the image. Then another feature(s) is extracted from the identified candidate object region. Based on the features extracted in these two stages, a target object region in the image and a confidence for the target object region are determined. In this way, the features that characterize the image from the whole scale and a local scale are both taken into consideration in object recognition, thereby improving accuracy of the object detection.