Abstract: A watermark detection method includes identifying, among plural stored videos, a second video having a second video feature matching a first video feature of a first video, the second video comprising watermark information. The method further includes comparing the first video and the second video to obtain a video conversion parameter, the video conversion parameter indicating a difference between the first video and the second video. The method also includes converting the first video based on the video conversion parameter to obtain a third video, and performing watermark detection on the third video to obtain watermark information in the third video. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.

Abstract: Systems and methods for identifying a presence of a completed document are disclosed. The system may receive an image file from a client device associated with a first document, identify one or more image regions within the image file corresponding to a presence of one or more extractable data entries, selectively extract the one or more extractable data entries, and determine whether the one or more extractable data entries match one or more stored data entries. When the one or more extractable data entries match, the system may determine the status of the first document as completed. When the one or more extractable data entries do not match, the system may proactively replace one or more inconsistent extractable data entries with corresponding stored data entries to form a corrected first document, and generate a request for a client to verify the corrected first document.

Abstract: A system includes a first sensor configured to detect an object within an air space, and output an observation signal indicative of the object within the air space. A second sensor is configured to track the object within the air space, and output a tracking signal of the object within the air space. A tracking control unit is in communication with the first sensor and the second sensor. The tracking control unit is configured to receive the observation signal from the first sensor. In response to receiving the observation signal from the first sensor, the tracking control unit is configured to operate the second sensor to track the object within the air space relative to an aircraft within the air space. The tracking control unit is also configured to determine a priority of actions to take in relation to the object based, at least in part, on the tracking signal received from the second sensor.

Abstract: A method is provided to using a machine learning model to predict lane geometry where incorrect or missing lane line geometry is detected. Methods may include: receiving a representation of lane line geometry for one or more roads of a road network; identifying an area within the representation as broken lane line geometry of an intersection using a machine learning model; generating a masked area of the broken lane line geometry of the intersection within the representation; processing the representation with the masked area using an inpainting model to generate an inpainted result within the masked area of restored lane line geometry of the intersection, where the inpainting model is trained using a set of representations identified as lane line geometry of intersections; and updating a map database to include the restored lane line geometry of the intersection in place of the broken lane line geometry of the intersection.

Abstract: An image forming apparatus that cooperates with a management service and a blockchain service includes a generation unit that generates an embedded image from document information about a document, an acquisition unit that acquires an embedding setting for use in embedding the embedded image in the document, a printing unit that performs printing of the document with the embedded image embedded therein based on the embedding setting, and a registration unit that registers the document information with the blockchain service, wherein, while the embedding setting includes a setting for embedding a plurality of embedded images in the document and the printing unit outputs a printed product with a plurality of embedded images embedded therein, the registration unit registers the document information with the blockchain service in such a way as to prevent the document information from being registered in an overlapping manner in registering the document information.

Abstract: A multimodal inspection system (MIS) is disclosed herein. The MIS may use one or more modalities to inspect a sample. Some of the modalities include, but are not limited to, Raman, visible (VIS), terahertz (THz) spectroscopy, longwave infrared (LWIR), shortwave infrared (SWIR), laser profilometry (LP), electromagnetic interference (EMI) near field probing, and/or, Millimeter Wave (MMW) radar.

Abstract: Process for interpreting one or more borehole images for use in drilling operations. In some embodiments, the process can include providing an input borehole image obtained from a downhole measurement provided by one or more downhole sensors. The process can also include collecting contextual information relative to the borehole image and the user. The process can also include using the collected contextual information and a mathematical model to infer one or more processing arguments. The mathematical model can be defined by using previously collected arguments and previously collected contextual information. The process can also include processing the input borehole image with the one or more inferred processing arguments to generate one or more interpreted borehole images. The process can also include adjusting one or more drilling operation based, at least in part, on the one or more interpreted borehole images.

Abstract: Systems and methods are disclosed for analyzing an image of a slide corresponding to a specimen, the method including receiving at least one digitized image of a pathology specimen; determining, using the digitized image at an artificial intelligence (AI) system, at least one salient feature, the at least one salient comprising a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and/or cancer sub-type; determining, at the AI system, a salient region overlay for the digitized image, wherein the AI system indicates a value for each pixel; and suppressing, based on the value for each pixel, one or more non-salient regions of the digitized image.

Abstract: Systems, methods, and computer program products for fugitive emission determinations are provided. An example imaging system includes a first infrared (IR) imaging device configured to generate first IR image data of a field of view of the first IR imaging device that include one or more data entries associated with a fugitive emission from an emission source. The system further includes a computing device operably connected with the first IR imaging device and configured to receive the first IR image data from the first IR imaging device, generate spectral absorption data based on the first IR image data, and determine a gas amount associated with the fugitive emission based upon the spectral absorption data. The computing device also determines a leak rate and leak duration of the fugitive emission based upon the determined gas amount and determines a total emission loss based on the same.

Abstract: A system, method and computer program product for protecting a deep neural network image classifier against receiving perturbed images. A plurality of watermark bits are embedded into an original digital image intended for the deep neural network image classifier. The watermarked image is transmitted through a potentially adversarial environment. A potentially perturbed image intended for the deep neural network image classifier is received from the potentially adversarial environment. The potentially perturbed image is determined to be an adversely modified or benign image by determining whether the potentially perturbed image includes a plurality of embedded bits matching the plurality of watermark bits embedded into the original digital image. The potentially perturbed image is prevented from being provided to the deep neural network image classifier in response to determining that the potentially perturbed image is the adversely modified image.

Abstract: Systems and methods for conducting a cloud-based forensic investigation of electronically-stored information are provided. The system includes an investigation requestor device configured to request a forensic investigation including selecting search criteria for the investigation, at least one remote system of the target, wherein the at least one remote system comprises electronically-stored information; a cloud server for storing forensic artifacts collected from the at least one remote system, wherein the forensic artifacts are collected based on the search criteria; and a cloud-based evidence-processing service configured to analyze the forensic artifacts and generate an initial report.

Abstract: This facial authentication device is provided with: a detecting means for detecting a plurality of facial feature point candidates, using a plurality of different techniques, for at least one facial feature point of a target face, from a plurality of facial images containing the target face; a reliability calculating means for calculating a reliability of each facial image, from statistical information obtained on the basis of the plurality of detected facial feature point candidates; and a selecting means for selecting a facial image to be used for authentication of the target face, from among the plurality of facial images, on the basis of the calculated reliabilities.

Abstract: Provided is a tape inspection device. The tape inspection device according to the present invention includes: a vision unit for acquiring imaging information by imaging a tape attached to an outer wall of a secondary battery in order to fix a folding portion of the secondary battery; a light reflection unit disposed to be spaced apart from the secondary battery and reflecting light; and an optical path compensation unit disposed between the vision unit and the light reflection unit and compensating for an optical path between the tape and the vision unit.

Abstract: Disclosed herein are a contour-based privacy region masking apparatus and method. The contour-based privacy region masking apparatus includes a memory for storing at least one program, and a processor for executing the program, wherein the program may perform detecting a contour of an object that is a privacy protection target in an original image, setting a masking region based on the detected contour, and de-identifying the masking region in the original image.

Abstract: Systems and methods for providing multi-factor authentication based on visual objects associated with an out of band shared secret delivery channel and at least one user device of a telecommunication network include an access point communicatively coupled to an authentication system. The authentication system is structured to generate a set of visual objects, cause the set of visual objects to be output by a first user device, transmit, via an out of band shared secret delivery channel, a visual object request to cause a secondary user device to output one or more out of band visual objects, receive an indication of object selection from the set of visual objects, determine that the indication of the object selection is associated with a visual selection match among the set of visual objects, and based on the visual selection match, authenticate access to an application associated with the authentication system.

Abstract: The noise reduction convolutional auto-encoding method includes the following tasks. A distorted image is received and input into a noise reduction convolutional auto-encoding model. In the noise reduction convolutional auto-encoding model, an image feature of the distorted image is transferred to a first deconvolution layer through skip-connection. A plurality of multi-stride encoding convolutional layers are performed for the distortion image to reduce a dimension. A same-dimensional encoding convolutional layer is then performed. According to the corresponding multi-stride encoding convolutional layers and same-dimensional encoding convolutional layers, the corresponding a plurality of decoding multi-stride convolutional layers and a same-dimensional decoding convolutional layers are upgraded. The result of up-scaled dimension is input into the same-dimensional decoding convolutional layer of a balanced channel using the first deconvolution layer.

Abstract: This application provides a semantic segmentation network structure generation method performed by an electronic device, and a non-transitory computer-readable storage medium.

Abstract: A computer implemented method and system for identifying and visualizing features correlated with cancer subtypes, includes the steps of receiving a set of medical images representing an area including a patient's lesion, applying a classification model trained on lesions with known pathology by mathematically combining the model's learned weights with said medical images to produce a score indicating the likelihood of the lesion being of each particular cancer subtype, extracting importance maps from said classification model indicating features correlated with each cancer subtype by tracing the output of the model through the learned weights to identify regions of the input with a strong influence on the classification score for each cancer subtype, and displaying said importance maps visually on a computing device.

Abstract: The disclosure relates to method and system for evaluating luminance in Augmented Reality (AR) applications. The method includes receiving a plurality of video frames corresponding to an AR object in a real-world environment at a current camera angle; for each of the plurality of video frames, subtracting the set of AR object pixels from the set of environment pixels in a frame; calculating mean luminance value corresponding to the set of AR object pixels in each of the at least one of the plurality of blocks in the frame and corresponding to each of the plurality of blocks of the grid in the real-world environment through a light sensor; comparing mean luminance value for each of the plurality of blocks of the grid with mean luminance value corresponding to the set of AR object pixels; and evaluating luminance of AR object at the current location in the AR application.

Abstract: An image forming apparatus includes a first printer configured to print on a medium using a first material, a second printer configured to print on the medium using a second material that turns invisible when a first condition is satisfied, and a controller configured to: control the first printer to print on the medium a first symbol that is machine-readable and associated with first information, and control the second printer to print a second symbol on the medium on which the first symbol has been printed. A composite symbol of the first and second symbols is machine-readable and associated with second information different from the first information.

Abstract: An image processing method includes obtaining a sample image and a generative adversarial network (GAN), including a generation network and an adversarial network, and performing style conversion on the sample image, to obtain a reference image. The method further includes performing global style recognition on the reference image, to determine a global style loss between the reference image and the sample image, and performing image content recognition on the reference image and the sample image, to determine a content loss between the reference image and the sample image. The method also includes performing local style recognition on the reference image and the sample image, to determine a local style loss of the reference image and a local style loss of the sample image, training the generation network to obtain a trained generation network, and performing style conversion on a to-be-processed image by using the trained generation network.

Abstract: A method and device for image generation are provided. The method includes: obtaining a text describing a content of an image to be generated; extracting, using a text encoder, a text feature vector from the text; determining a semantic mask as spatial constraints of the image to be generated; and automatically generating the image using a generative adversarial network (GAN) model according to the semantic mask and the text feature vector.

Abstract: Techniques are disclosed for implementing a convolutional neural network that determines an offset field for deforming a kernel to be used in a convolution. The offset field is temporally-based, at least in part, on data generated at an earlier time. Furthermore, techniques are disclosed for using sensor data to train a neural network to learn shapes or configurations of such deformed kernels. The temporal-based deformable convolutions may be used for object identification, object matching, object classification, segmentation, and/or object tracking, in various examples.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for processing a target object. The method includes acquiring an initial non-video feature vector on the basis of at least one input of a received speech input and text input. The method further includes taking, in response to not receiving a video input, a default feature vector as an initial video feature vector corresponding to the video input. The method further includes generating a video feature, a speech feature, and a text feature on the basis of the initial non-video feature vector and the initial video feature vector. The method further includes generating a processing parameter for a target object on the basis of the video feature, the speech feature, and the text feature, wherein the processing parameter includes at least one of an emotion parameter, an attribute parameter, and a pose parameter.

Abstract: An image augmentation method applied to an electronic device is provided. The method includes constructing a variational learner and a discriminator based on a fully convolutional neural network. A target image is obtained by inputting a gas leakage image into the variational learner. A variational autoencoder model is obtained by training the variational learner based on a discrimination result of the discriminator on the target image. A reconstruction accuracy rate is calculated based on a test image, an augmented model is obtained by adjusting the variational autoencoder model based on the gas leakage image, in response that the reconstruction accuracy rate being less than a preset threshold; and an augmented image is obtained by inputting the image to be augmented into the augmented model.

Abstract: A system and method for managing encoded information in a real-time screen-to-camera communication environment are disclosed. The system converts information into a pre-defined number of characters and generates data symbols in shapes and pilot symbols corresponding to the characters. Further, the system embeds the data symbols in media content frames and modulates pixels and boundaries for display of display device, based on luminance, and adaptively displays frames as temporal-complementary frames. Furthermore, the system detects frames from recorded content, extracts data symbols based on grid and fixed pattern, and detects bit values by analyzing color differences. Additionally, the system generates information based on the detected bit values and outputs the information on an user device display, including products, recommendations, services, and relevant information related to the media content.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to monitor streaming media content. Example apparatus disclosed herein include means for determining whether a streaming media flag is asserted in a payload of a watermark detected in media presented by a media presentation device, the streaming media flag to indicate whether the media was distributed to the media presentation device as streaming media. Disclosed example apparatus also include means for discarding the detected watermark from collected data in response to a determination that the streaming media flag is asserted. Disclosed example apparatus further include means for reporting the collected data to a remote server via a network.

Abstract: A computer-implemented method according to one embodiment includes receiving, at a scheduler, a training data instance and a target instance, generating, by the scheduler, an input sequence from the training data instance and the target instance, sending the input sequence from the scheduler to an encoder, mapping, by the encoder, the input sequence to a feature vector, sending the feature vector from the encoder to the scheduler, sending the feature vector from the scheduler to a predictor, and mapping, by the predictor, the feature vector to a class vector to create a label for the target instance.

Abstract: The present disclosure discloses an optical imaging lens assembly including, sequentially from an object side to an image side along an optical axis, a first lens having positive refractive power and a concave image-side surface; a second lens having refractive power and a concave image-side surface; a third lens having refractive power; a fourth lens having refractive power; a fifth lens having positive refractive power; a sixth lens having refractive power, a convex object-side surface and a concave image-side surface; and a seventh lens having refractive power and a concave object-side surface. Half of a maximum field-of-view HFOV of the optical imaging lens assembly and a total effective focal length f of the optical imaging lens assembly satisfy: tan(HFOV)*f?4.34 mm.

Abstract: To provide more test data during the manufacture of non-volatile memories and other integrated circuits, machine learning is used to generate virtual test values. Virtual test results are interpolated for one set of tests for devices on which the test is not performed based on correlations with other sets of tests. In one example, machine learning determines a correlation study between bad block values determined at die sort and photo-limited yield (PLY) values determined inline during processing. The correlation can be applied to interpolate virtual inline PLY data for all of the memory dies, allowing for more rapid feedback on the processing parameters for manufacturing the memory dies and making the manufacturing process more efficient and accurate. In another set of embodiments, the machine learning is used to extrapolate limited metrology (e.g., critical dimension) test data to all of the memory die through interpolated virtual metrology data values.

Abstract: Apparatuses, methods, and systems are disclosed for estimating a trajectory path of an object. An apparatus includes an object module that identifies a target object based on data captured from a first sensor. An apparatus includes a location module that identifies the target location for the target object based on data captured from a second sensor. An apparatus includes a path module that determines an objective path for the target object relative to the target location. An apparatus includes a surface module that identifies a surface of a striking object that is configured to cause the target object to move along a trajectory path towards a target location. A path module estimates the trajectory path of the target object towards the target location and relative to the objective path prior to the striking object contacting the target object.

Abstract: An electronic apparatus is disclosed. The electronic apparatus includes a memory configured to store a plurality of neural network models, and a processor connected to the memory and control the electronic apparatus in which the processor is configured to obtain a weight map based on an object area included in an input image, and obtain a plurality of images by inputting the input image to each of the plurality of neural network models, and obtain an output image by weighting the plurality of images based on the weight map, and each of the plurality of neural network models is a model trained to upscale an image.

Abstract: A method provides a display of vehicle surroundings in a vehicle by detecting the degree of automation at which the vehicle is operated, selecting a set of additional information from one of multiple possible sets of additional information on the basis of the detected degree of automation, wherein each set of additional information includes a different number of pieces of additional information, each piece of additional information describes a display option which visualizes the current state of the vehicle and the corresponding vehicle surroundings, and a set of additional information selected for a low degree of automation includes less additional information than a set of additional information selected for a degree of automation which is higher than the low degree of automation; and displaying a view of the surroundings of the vehicle. The additional information of the selected set of additional information is visualized in the displayed view.

Abstract: A method of semiconductor metrology includes patterning a film layer on a semiconductor substrate to define a first field on the semiconductor substrate with a first pattern comprising at least a first target feature within a first margin along a first edge of the first field and to define a second field, which abuts the first field, with a second pattern comprising at least a second target feature within a second margin along a second edge of the second field, such that the second edge of the second field adjoins the first edge of the first field. The first target feature in the first margin is adjacent to the second target feature in the second margin without overlapping the second target feature. An image is captured of at least the first and second target features and is processed to detect a misalignment between the first and second fields.

Abstract: A computer-implemented method of reconstructing boundaries from a computed tomography (CT) image dataset is provided. The method comprises receiving CT image data and applying a number of image filters to the CT image data. A numerical derivative is applied to the filtered CT image data to flatten and suppress non-edge regions that do not correspond to edges. Numerical derivative values are clipped to a specified range to reduce artifacts and noise, and an X-ray image is reconstructed according to the image filters and clipped numerical derivative values.

Abstract: A method according to an embodiment of the present disclosure includes obtaining proof data including a photographed image and a challenge code for proving original of the image, generating hash data by using the proof data, generating signature data for the hash data, transmitting the proof data, the hash data, and the signature data to a server, and receiving an access path to an original verification result of the proof data from the server.

Abstract: A method for encapsulating a video bit-stream in a server, including obtaining at least one network abstraction layer unit (NAL unit) of a first picture, buffering the at least one obtained NAL unit, obtaining at least one NAL unit of a second picture, the second picture being a random access picture following the first picture, and encapsulating the at least one obtained NAL unit of the second picture and the at least one buffered NAL unit in an encapsulation structure making it possible to generate a video bit-stream without processing the encapsulated at least one buffered NAL unit when processing the encapsulated video bit-stream.

Abstract: In picking up tools in an automatic milking arrangement, the positions of the tools are determined by registering, via a camera at an origin location, three-dimensional image data representing the tools whose positions are to be determined. Using an algorithm involving matching the image data against reference data, tool candidates are identified in the three-dimensional image data. A respective position is calculated for the tools based on the origin location and data expressing respective distances from the origin location to each of the identified tool candidates. It is presumed that the tools have predefined locations relative to one another. Therefore, any second tool candidate is disregarded, which is detected at a separation distance from a first tool candidate when the separation distance exceeds a first threshold distance in relation to the predefined relative locations.

Abstract: A processing method includes obtaining a processing image of a apparatus and performing a second processing on the processing image to generate a target image to analyze the target image according to a target defect detection method to realize defect detection of the apparatus. The processing image is obtained by performing a first processing on an initial image of the apparatus. The first processing includes performing scale processing on the initial image according to defect parameters corresponding to the initial image.

Abstract: A tangible, non-transitory machine-readable medium includes machine readable instructions that, when executed by processing circuitry, cause the processing circuitry to receive an inquiry regarding digital content. The inquiry is indicative of a request for the digital content or a request for a determination to be made regarding the digital content. The instructions, when executed, also cause the processing circuitry to process the inquiry by analyzing aggregated result data generated using a series of neural network layers based on the digital content and metadata associated with the digital content. Furthermore, the instructions, when executed, cause the processing circuitry to generate response data to the inquiry using a neural network based on analyzing the aggregated result data.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: The image analysis method of the disclosure includes following steps: obtaining an image of a multi-layer structure provided by an electron microscope and displaying the image of the multi-layer structure through a display device, wherein the image of the multi-layer structure is a gray-scale image; setting a measurement line segment on the image of the multi-layer structure, wherein the measurement line segment extends along a first direction; detecting a gray-scale distribution within the measurement line segment corresponding to the image of the multi-layer structure along the measurement line segment; and analyzing the gray-scale distribution to determine a plurality of dark layer thicknesses and a plurality of light layer thicknesses according to a threshold range.

Abstract: A deep neural network(s) (DNN) may be used to detect objects from sensor data of a three dimensional (3D) environment. For example, a multi-view perception DNN may include multiple constituent DNNs or stages chained together that sequentially process different views of the 3D environment. An example DNN may include a first stage that performs class segmentation in a first view (e.g., perspective view) and a second stage that performs class segmentation and/or regresses instance geometry in a second view (e.g., top-down). The DNN outputs may be processed to generate 2D and/or 3D bounding boxes and class labels for detected objects in the 3D environment. As such, the techniques described herein may be used to detect and classify animate objects and/or parts of an environment, and these detections and classifications may be provided to an autonomous vehicle drive stack to enable safe planning and control of the autonomous vehicle.

Abstract: A method for determining the validity of a parallax image including receiving a captured two-dimensional image of a parallax image having at least three target identifiers, where at least two target identifiers are located at different depth planes in the parallax image; identifying the at least three target identifiers in the captured two-dimensional image of the parallax image and determining the spatial relationship between the at least three target identifiers in the two-dimensional image of the parallax image; comparing the spatial relationship of the at least three target identifiers in the captured two-dimensional image of the parallax image against a predetermined spatial relationship of the at least three target identifiers that indicates authenticity; and adjudicating the authenticity of the parallax image based on the degree of difference between the spatial relationship of the at least three target identifiers in the captured two-dimensional image and the predetermined spatial relationship.

Abstract: Systems and methods are described for obfuscating variants of content segments. Variants of content segments can be used to encode an identifying sequence in a transmission of content. The variants of the content segments can each include one or more marked frames and one or more unmarked frames. Variations can be introduced into the unmarked frames for each of the variants of the content segments.

Abstract: The present disclosure discloses a media monitoring method, apparatus and system. The method includes: obtaining image information of a program verification region in a display frame of a currently monitored display screen, wherein the program verification region is configured to display verification information corresponding to a current program that should be broadcast on the display screen; identifying the image information to determine actual display information representing a current actually-broadcast program; and performing verification on the actual display information according to the verification information, and determining that the display screen broadcasts normally if the verification is passed, or determining that the display screen does not broadcast normally if the verification is failed.

Abstract: A visual tracking system for tracking and identifying persons within a monitored location, comprising a plurality of cameras and a visual processing unit, each camera produces a sequence of video frames depicting one or more of the persons, the visual processing unit is adapted to maintain a coherent track identity for each person across the plurality of cameras using a combination of motion data and visual featurization data, and further determine demographic data and sentiment data using the visual featurization data, the visual tracking system further having a recommendation module adapted to identify a customer need for each person using the sentiment data of the person in addition to context data, and generate an action recommendation for addressing the customer need, the visual tracking system is operably connected to a customer-oriented device configured to perform a customer-oriented action in accordance with the action recommendation.

Abstract: Methods and systems for rendering a gloss effect can involve determining among a first color and a second color, which of the first color or the second color is mixed with a black colorant that is furthest from a rich black colorant; selecting a first color with the black colorant; selecting a second color to be fully black and a least rich black colorant; creating an object with the first color and entering data within the object opaquely with the second color; and rendering a document with the object including the data with the object, wherein the object with the data can exhibit a gloss effect based on the first color and the second color.

Abstract: Systems and methods for automatically grading a user device are provided. Such systems and methods can include (1) a lighting element positioned at an angle relative to a platform, (2) an imaging device positioned at the angle relative to the platform such that light emitted from the lighting element and a field of view of the imaging device form a right angle where the light emitted from the lighting element and the field of view meet at a user device when the user device is positioned at a predetermined location on the platform, and (3) control circuitry that can activate the lighting element, instruct the imaging device to capture an image of a screen of the user device while the user device is at the predetermined location and is being illuminated by the first lighting element, and parse the image to determine whether the screen is damaged.

Abstract: A virtual wig display assembly includes a mirror and a display that is integrated into the mirror to display imagery. A first camera is integrated into the mirror to capture imagery of a user and a second camera is integrated into the mirror to capture imagery of the user. A plurality of light emitters is each attached to the mirror to emit light outwardly from the mirror. A transceiver is integrated into the mirror and the transceiver is in wireless communication with a personal electronic device for receiving a picture of a wig taken with the personal electronic device. The display superimposes the picture of the wig on a picture of the user thereby facilitating the user to view themselves with the wig.