Abstract: Various example embodiments relate to an electronic device for recognizing visual stimulus based on spontaneous selective neural response of deep artificial neural network and an operating method thereof, and may configured to measure a response of an untrained randomly-initialized neural network for an input image, and recognize at least one visual stimulus from the input image, based on the measured response.

Abstract: An image processing apparatus includes an acquisition unit configured to acquire reference data and image data representing an inspection target image, the reference data representing a reference image that is a reference printing result, a setting unit configured to set a detection sensitivity for a plurality of defects in a printing result, a correction unit configured to correct a difference image acquired from the reference data and the image data so that a difference in the difference image that is greater than a threshold value is reduced, and a processing unit configured to inspect the inspection target image based on the detection sensitivity and the corrected difference image.

Abstract: A three-dimension scanning apparatus and method of use is disclosed. The system includes a light intensity meter for measuring a level of light intensity at a first camera of the 3D scanning apparatus. The first camera has an adjustable aperture. A processor is provided that is configured to adjust the adjustable aperture of the first camera automatically based on the measured light level.

Abstract: An information processing device includes a storage section that stores a machine-learned model subjected to machine learning using teaching data in which at least one of an image included in read data of a document read by a scanner, a character string included in the read data, and a layout of the read data that is included in the read data is associated with a file name of the read data, and a controller that generates the file name of the read data using the machine-learned model and at least one of the image, the character string, and the layout that are included in the read data.

Abstract: Provided is an image processing device which has: an image input part configured to input a multi-spectral image which includes N (N is an integer of 4 or more) channels corresponding to N bands; a reference vector setting part configured to cause a user to set, as three reference vectors, three types of N-dimensional vectors having sensitivities of the respective N bands as elements; and a conversion part configured to convert the multi-spectral image into a 3-channel image including three channels by decomposing a spectral distribution of each pixel of the multi-spectral image on the basis of the three reference vectors.

Abstract: An image processing apparatus includes circuitry configured to receive a designation of a to-be-corrected color that is a process color or a special color different from the process color and is to be corrected; identify, on the basis of the designation, a tone correction pattern, and generate rendering data of the tone correction pattern to be used for forming an image on a recording medium; obtain a standard value of the to-be-corrected color; and correct the to-be-corrected color on the basis of a difference between a color measuring result obtained from measuring a color of the image, of the tone correction pattern formed on the recording medium and the standard value.

Abstract: The present disclosure discloses an error modeling method and device for prediction context of reversible image watermarking. A predictor based on omnidirectional context is established; then, the prediction context is self-adaptively error modeled to obtain a self-adaptive error model; and finally, output data from the self-adaptive error model is fed back to the predictor to update and correct the prediction context, so as to correct a prediction value of a current pixel x[i,j]. Since the non-linear correlation between the current pixel and the prediction context thereof, i.e., the non-linear correlation redundancy between pixels can be found by the error modeling of the prediction context of the predictor, the non-linear correlation redundancy between the pixels can be effectively removed. Thus, the embeddable watermarking capacity can be increased.

Abstract: Methods and systems for invisible watermarking of images and video are disclosed. According to one embodiment, a method for watermarking video comprises selecting a block corresponding to a subset of pixels in a video frame. The block has quantized coefficients generated during encoding of the block. A modification function is applied to a candidate quantized coefficient (QC) in the block to incorporate a bit of a watermark message. The modification function is based on a set of configuration parameters.

Abstract: A method for color correcting imagery is disclosed. A plurality of images of a scene having different levels of detail is received. A first color correction is determined based on a first reference image and a first target image. The first reference image has a first level of detail and the first target image has a second level of detail greater than the first level of detail. The first color correction is applied to the first target image to generate a first color-corrected image having the second level of detail. A second color correction is determined based on the first color-corrected image and a second target image. The second target image has a third level of detail greater than the second level of detail. The second color correction is applied to the second target image to generate a second color-corrected image.

Abstract: The disclosed systems, structures, and methods are directed to a digital watermarking system comprising: a data separator configured to receive a digital data file and segregate the digital data file into a message component and a data component, in which the message component includes a message, and the data component includes a data file; a message pipeline configured to process the message; a data pipeline configured to process the data file; a watermark pipeline configured to embed the processed message file onto the processed data file; and an inverse process pipeline configured to inverse the process applied by the data pipeline while processing the data file and generate a watermarked data file.

Abstract: A color prediction model creation device configured to create a color prediction model for predicting color values of a device-independent color system from an ink amount set includes: a first color prediction model creation unit configured to acquire a first spectral reflectance of a color chart printed on a first printing medium by using a first ink amount set, and create a first color prediction model for the first printing medium by learning a correspondence relationship between the first ink amount set and the first spectral reflectance; and a second color prediction model creation unit configured to acquire a second spectral reflectance of a color chart printed on a second printing medium by using a second ink amount set having a smaller number of combinations than that of the first ink amount set, and create a second color prediction model for the second printing medium by learning using the second ink amount set, the second spectral reflectance and the first color prediction model.

Abstract: A high-definition image is preprocessed to generate a substantially losslessly-reconstructable set of image components that include a relatively low-resolution base image and a plurality of extra-data images that provide for progressively substantially losslessly reconstructing the high-definition image from the base image, wherein a single primary-color component of the extra-data images provides for relatively quickly reconstructing full-resolution intermediate images during the substantially lossless-reconstruction process.

Abstract: An image forming apparatus includes a memory and a processor configured to output an image formed based on image data including predetermined specific text after replacing a color of one or more portions in the image data with a special color that is in advance associated with the specific text, the one or more portions being assigned a color identical or similar to a color of the specific text to form the image.

Abstract: For image captioning such as for computer game images or other images, bottom-up attention is combined with top-down attention to provide a multi-level residual attention-based image captioning model. A residual attention mechanism is first applied in the Faster R-CNN network to learn better feature representations for each region by taking spatial information into consideration. In the image captioning network, taking the extracted regional features as input, a second residual attention network is implemented to fuse the regional features attentionally for subsequent caption generation.

Abstract: Optical code signal components are generated and then transformed into signal bearing art that conveys machine readable data. The components of an optical code are optimized to achieve improved signal robustness, reliability, capacity and/or visual quality. An optimization program can determine spatial density, dot distance, dot size and signal component priority to optimize robustness. An optical code generator transforms tiles of an optical code or image embedded with the optical code into signal-bearing art using stipple, Voronoi, Delaunay or other graphic drawing methods so as to retain prioritized components of the optical code. The optical code is merged into a host image, such as imagery, text and graphics of a package or label, or it may be printed by itself, e.g., on an otherwise blank label or carton. A great number of other features and arrangements are also detailed.

Abstract: In one example, a system for measuring body movement in a movement disorder disease is provided. The system may comprise at least one processor and a memory storing processor executable codes, which, when implemented by the at least one processor, cause the system to perform operations comprising, at least receiving a video including a sequence of images and detecting at least one object of interest in one or more of the images. Feature reference points of the at least one object of interest are located, and a virtual movement-detection framework is generated in one or more of the images. The operations may include detecting, over the sequence of images, at least one singular or reciprocating movement of the feature reference point relative to the virtual movement-detection framework and generating a virtual path tracking a path of the at least one detected singular or reciprocating movement of the feature reference point.

Abstract: A method performs color control in a printing operation on a printing machine by use of a computer. The computer uses an input profile to transform print image data from a first color space to a device-independent color space, subsequently uses an output profile to transform the print image data into a second color space dependent on the printing machine. The computer compares measurement conditions of the used input profile and of the output profile to be generated, and, if there are differences between the respective measurement conditions, adapts the print image data in the device-independent color space to deviating measurement conditions of the output profile. The printing machine subsequently executes the printing operation using the print image data, and wherein UV light excitation is used for the measurement conditions of the output profile.

Abstract: The present disclosure provides systems and methods for color prediction. The systems and methods can be configured to utilize machine learning and user input data to generate color transformation process, whereby perceived colors between images may be indistinguishable from one another despite having different color model values, thereby improving and rendering more accurate or desired color perception to an end-user.

Abstract: The occurrence of image quality adverse effects, such as interference fringes and color bleeding, is suppressed for an object including a spot color adjustment-target color. In a case where a spot color adjustment function is made use of, the same color separation table is caused to be applied uniformly, instead of switching color separation tables to be applied to an adjustment-target color depending on whether the object attribute is text/line/graphics, or image.

Abstract: A skin color image gamut weight detecting method and a device thereof are provided. The method includes: receiving an image including first color components and second color components; obtaining a skin color region, a skin color category, and a first gamut; obtaining first color component values and first cardinal numbers according to the first color components; obtaining second color component values and a plurality of second cardinal numbers according to the second color components; obtaining a second gamut and a weight center according to the skin color category, the first cardinal numbers, the second cardinal numbers, the first color component values, and the second color component values; obtaining a first weight area and a second weight area according to the first gamut and the second gamut; and obtaining a skin color gamut weight map according to the weight center, the first weight area, and the second weight area.