Abstract: An adaptive automobile meter detection method based on character segmentation cascade classifier which processes threshold segmentation, morphology and connected components analysis on the original image; extracts the pointer based on the contour analysis method, establishes a pointer information list; constructs a character segmentation cascade classifier by combining a HOG/SVM character segmentation classifier, a character filter and a CNN digit classifier. The character segmentation cascade classifiers is used to identify the digit character area of the automobile meter. Region analysis is performed to extract tick marks based on the center of the digit character area. The angular position corresponding to the tick mark is determined. The response value corresponding to the pointer is determined by establishing the Newton interpolation linear description relationship between the pointer angle and the response value and then the meter is classified as pass or fail.

Abstract: A document source identification system includes one or more memory devices storing instructions, and one or more processors configured to execute the instructions to cause the system to receive uploaded document(s) having at least one extractable data entry. The system may categorize the document, and extract at least one data entry from the document. The system may normalize each extracted data entry and execute a deterministic ID search to determine that the normalized data entry matches zero, one, or more than one account data entries associated with user accounts. Responsive to an exact match, the system may link the uploaded document to a user account associated with the matching data entry. Responsive to zero or multiple matches, the system may execute a probabilistic ID search identifying a highest ranked user account data entry and link the document to a user account associated with the highest ranked user account data entry.

Abstract: A method for information processing includes a learning process to generate a tree structured dictionary based on a plurality of patterns including a target object to be recognized. The method includes selecting a plurality of points from an input pattern based on a distribution of a probability that the target object to be recognized is present in the input pattern at each node of a tree structure generated in the learning process, and classifying the input pattern into a branch based on a value of a predetermined function that corresponds to values of the input pattern at selected plurality of points.

Abstract: An information processing apparatus that estimates waiting time in a waiting line with improved accuracy includes a first acquisition unit that acquires a number of objects in the waiting line, a second acquisition unit that acquires frequency of an object exiting the waiting line, and an estimation unit that estimates waiting time in the waiting line based on the acquired number of objects in the waiting line and the acquired frequency of an object exiting the waiting line.

Abstract: A drug inspection apparatus inspects drugs that are prepared based on prescription information and are packaged in a prescription bag. A drug database includes drug images of drugs that can be prepared. A comparison target selection section acquires drug images of drugs, which are prepared according to the prescription, and drugs similar thereto from the drug database. A first drug determination section compares captured images of prepared drugs with the drug images acquired from the drug database, and determines drugs present in the captured images and the number thereof. An inspection result determination section determines whether or not the prepared drugs and the number thereof match the prescription information based on the prescription information.

Abstract: An image recognition apparatus is provided which comprises a first extracting means for extracting, from every registration image previously registered, a set of registration partial images of a predetermined size, and a second extracting means for extracting, from an input new image, a set of new partial images of a predetermined size. The apparatus further comprises a discriminating means for discriminating an attribute of the new partial image based on a rule formed by dividing the set of the registration partial images extracted by the first extracting means, and a collecting means for deriving a final recognition result of the new image by collecting discrimination results by the discriminating means at the time when the new partial images as elements of the set of the new partial images are input.

Abstract: A computer-based system and method for taking clarity measurements of a gem, and a computer-readable medium having computer-executable instructions, are provided and include receiving a pixilated image of a gem and identifying pixels representing an inclusion. The method and medium further include determining characteristics of the inclusion as a function of the pixels representing the inclusion, and providing a clarity grade based upon the determined characteristics. Also provided is a method for mapping a gem, and a computer-readable medium having computer-executable instructions, which include receiving a pixilated image of a gem having facet edges, and identifying pixels representing the facet edges. The method and medium further include generating a diagram of the gem, such that the diagram is a function of the pixels representing the facet edges, and superimposing the diagram onto the pixilated image.

Abstract: Implementations relate to removal of one or more images from a view of a plurality of images. In some implementations, a method includes obtaining a plurality of images, programmatically analyzing the plurality of images to determine a plurality of image features, and determining one or more image categories for the plurality of images based on the image features. The method further includes identifying a subset of the plurality of images based on the image categories, wherein each image of the subset is associated with an image category for archival. The method further includes causing a user interface to be displayed that includes one or more images of the subset, receiving user input to archive at least one of the one or more images, and in response to the user input, removing the at least one of the images from a view of the plurality of images.

Abstract: A computer-implemented method is disclosed for image recognition and other applications. The method employs an SVM model and can reduce false negatives and increase recognition accuracies by raising the sample-to-support-vector ratio.

Abstract: Four computerized machine learning methods for deep semantic segmentation are fast machine learning method, active machine learning method, optimal machine learning method, and optimal transfer learning method. The fast machine learning method performs a fast deep semantic segmentation learning on training images to generate a deep model. The active machine learning method performs a fast deep semantic segmentation learning on initial training images to generate a first deep model and then an active deep semantic segmentation learning to generate a second deep model. The optimal machine learning method performs a fast deep semantic segmentation learning on initial training images to generate a first deep model and then an optimal deep semantic segmentation learning to generate a second deep model. The optimal transfer learning method applies a pre-trained first deep model on transfer training images and then an optimal deep semantic segmentation transfer learning to generate a second deep model.

Abstract: Methods and electronic devices are provided in which first fingerprint information of a first portion of the user's fingerprint is obtained upon the user's fingerprint contacting the fingerprint sensor. A display object is output within a target area for the fingerprint registration, in response to obtaining the first fingerprint information. A guiding object is output to guide contact of a next portion of the user's fingerprint that is adjacent to the first portion. Next fingerprint information of the next portion of the user's fingerprint is obtained upon the user's fingerprint contacting the fingerprint sensor guided by the guiding object. Upon modifying the display object based on the obtained next fingerprint information, the steps of outputting a guiding object and obtaining a next fingerprint information are repeated until fingerprint information at least partially surrounding the first portion is obtained.

Abstract: Provided is an image processing system which determines at least one object using a low function device and a high function device having higher calculation capacity than the low function device. The low function device includes a part configured to output a first determination result which identifies the objects by applying a first convolution neural network to captured images of the objects, and a part configured to output the captured image to the high function device when the first determination result meets a predetermined condition. The high function device includes a part configured to apply a second convolution neural network preliminarily learned from a sample which is at least partially common to the first neural network to the captured image and to output a second determination result which identifies the object.

Abstract: A method includes identifying one or more first devices contained in at least one image captured by a mobile device. The method also includes obtaining data associated with at least one of: the one or more first devices and one or more second devices connected to or interacting with the one or more first devices. The method further includes presenting information overlaid over the at least one image by the mobile device to a user, where the presented information includes the data or information based on the data. The presented information varies based on perceived distance or proximity of the mobile device to the one or more first devices.

Abstract: An apparatus includes a first circuit and a second circuit. The first circuit may be configured to calculate a feature descriptor for each pixel of an image. The feature descriptor generally comprises sixteen discriminative feature values. The feature values are generally computed based on arithmetic combinations of a number of neighboring pixels at predetermined locations around each pixel. The second circuit may be configured to implement a color classification process combining multiple weak depth-two decision trees in a cascade. The second circuit may generate a plurality of likelihood values expressing a likelihood of a specific color road marking at each pixel location of the image using the feature descriptor of each pixel of the image.

Abstract: Methods, apparatuses and electronic devices for generating a feature vector, as well as searching methods, apparatuses and electronic devices are disclosed. The method for generating a feature vector includes: acquiring data information; extracting a semantic feature from the data information, to acquire semantic feature information; and acquiring a feature vector of the data information by using a preset function, with the semantic feature information as a parameter. The technical solution identifies picture information by recognizing semantics of image information and matching the semantics of the image information with natural language descriptions. Different from conventional image search schemes of existing search engines, this technical solution does not need to retrieve a text description of image information, but retrieves and identifies images based on the content of the image information. Therefore, results with higher accuracy may be returned compared with the existing text-based image search.

Abstract: Apparatus and methods for detecting and utilizing saliency in digital images. In one implementation, salient objects may be detected based on analysis of pixel characteristics. Least frequently occurring pixel values may be deemed as salient. Pixel values in an image may be compared to a reference. Color distance may be determined based on a difference between reference color and pixel color. Individual image channels may be scaled when determining saliency in a multi-channel image. Areas of high saliency may be analyzed to determine object position, shape, and/or color. Multiple saliency maps may be additively or multiplicative combined in order to improve detection performance (e.g., reduce number of false positives). Methodologies described herein may enable robust tracking of objects utilizing fewer determination resources. Efficient implementation of the methods described below may allow them to be used for example on board a robot (or autonomous vehicle) or a mobile determining platform.

Abstract: A method and system for processing an image operates by: filtering a first real image to obtain a first feature map therefor with performances of image features improved; upscaling the obtained first feature map to improve a resolution thereof, the feature map with improved resolution forming a second feature map; and constructing, from the second feature map, a second real image having enhanced performances and a higher resolution than that of the first real image.

Abstract: Aspects of the disclosure provide a method for processing an electronic mirror image. The method can include receiving a face-included image from an electronic mirror, and determining a face model that matches the face-included image. A user identity associated with the matched face model can then be obtained. A notification is sent to a terminal corresponding to the associated user identity. The notification indicates the face-included image has been obtained at the electronic mirror.

Abstract: There is provided an image processing apparatus in which a part used in predetermined processing is specified with use of a relatively small binarization threshold, from parts that have been converted into black pixels through binarization processing using a relatively large binarization threshold.

Abstract: A human detection system may detect the presence of a human around a shovel by using an image captured by an imaging device that is attached to the shovel and that captures a human from diagonally above. The human detection system may have an extracting part that extracts a part of the captured image as a target image, and an identifying part that identifies whether an image included in the target image extracted by the extracting part is an image of a human by an image processing. A target image region in the captured image corresponds to a virtual plane region having a predetermined size in a real space. In the real space, the virtual plane region faces toward the imaging device and is inclined with respect to a horizontal surface.