Abstract: A system and method include receiving target image data associated with a target coating. A feature extraction analysis process is applied to the target image data to determine a target image feature. The feature extraction analysis process includes dividing the target image into sub-images which contains a plurality of target pixels. A machine learning model identifies one or more types of flakes present in the target coating using target pixel features.

Abstract: Methods, systems, and apparatus including computer programs encoded on a computer storage medium, for generating convex decomposition of objects using neural network models. One of the methods includes receiving an input that depicts an object. The input is processed using a neural network to generate an output that defines a convex representation of the object. The output includes, for each of a plurality of convex elements, respective parameters that define a position of the convex element in the convex representation of the object.

Abstract: Methods, apparatus, and processor-readable storage media for character-based representation learning for table data extraction using artificial intelligence techniques are provided herein.

Abstract: A delivery system may include a pallet wrapper system having a turntable, a camera directed toward an area above the turntable, and a stretch wrap dispenser adjacent the turntable. A computer receives images from the camera of multiple sides of a pallet loaded with packages on the turntable. The computer stitches images from different sides of the stack of packages that correspond to the same package. At least one machine learning model may be used to infer SKUs of each package. Optical character recognition may be performed in parallel on the images. The determination of the SKU of each package may be based upon the inferred SKUs and on the OCR.

Abstract: Examples disclosed herein may involve a computing system that is operable to (i) receive one or more images related to a global map having a plurality of overlapping map segments, wherein each of the plurality of overlapping map segments overlaps with one or more neighboring map segments, (ii) based on a preliminary location determination for the one or more images, identify at least a first overlapping map segment of the plurality of overlapping map segments that corresponds to the one or more images, (iii) generate a reconstruction of the first identified overlapping map segment based on the one or more images, and (iv) fuse the generated reconstruction of the first identified overlapping map segment together with the first identified overlapping map segment's one or more neighboring map segments based on overlapping map portions between the generated reconstruction and the first identified overlapping map segment's one or more neighboring map segments.

Abstract: This disclosure provides methods, devices, and systems for low-light imaging. In some implementations, an image processor may be configured to reduce or remove noise associated with an image based, at least in part, on a neural network. For example, the neural network may be trained to infer a denoised representation of the image. In some aspects, the image processor may scale the brightness level of the image to fall within a normalized range of values associated with the neural network. In some other aspects, a machine learning system may scale the brightness levels of input images to match the brightness levels of ground truth images used to train the neural network. Still further, in some aspects, the machine learning system may scale the brightness levels of the input images and the brightness levels of the ground truth images to fall within the normalized range of values during training.

Abstract: Methods and apparatus for enhancing optical images and parametric databases are disclosed. In an exemplary embodiment, a method includes identifying an image and deconstructing the image into a frequency-based spatial domain representation utilizing a pyramidal data structure including a plurality of levels on a frequency-by-frequency basis. The method also includes modifying the frequency-based spatial domain representation to generate a modified frequency-based spatial domain representation, reconstructing an enhanced image from the modified frequency-based spatial domain representation, and returning the enhanced image. In an exemplary embodiment, an apparatus includes a deconstructor that deconstructs an image into a frequency-based spatial domain representation utilizing a pyramidal data structure including a plurality of levels on a frequency-by-frequency basis and a modifier that modifies the frequency-based spatial domain representation to generate a modified representation.

Abstract: Provided herein are systems and methods for extracting text from a document. Different optical character recognition (OCR) tools are used to extract different versions of the text in the document. Metrics evaluating the quality of the extracted text are compared to identify and select higher quality extracted text. A selected portion of text is compared to a threshold to ensure minimal quality. The selected portion of text is then saved. Error correction can be applied to the selected portion of text based on errors specific to the OCR tools or the document contents.

Abstract: Aspects of the present disclosure are directed to extracting textual information from image documents. In one embodiment, a system, upon receiving a request to extract textual information from an image document, a digital processing system performs character recognition based on content of the image document using multiple approaches to generate corresponding texts. The texts are then combined to determine a result text representing the textual information contained in the image document. The result is then provided as a response to the request.

Abstract: Exemplary embodiments may provide an approach to converting multidimensional color data for an image encoded in a first color space into an intermediate form that is a single dimensional value. The exemplary embodiments may then decode the intermediate form value to produce an encoding of the color data that is encoded in a second color space that differs from the first color space. In this manner, the data for the image may be efficiently converted from an encoding in the first color space into an encoding in the second color space.

Abstract: In various examples, two or more cameras in an automotive surround view system generate two or more input images to be stitched, or combined, into a single stitched image. In an embodiment, to improve the quality of a stitched image, a feedback module calculates two or more scores representing errors between the stitched image and one or more input images. If a computed score indicates structural errors in the stitched image, the feedback module calculates and applies one or more geometric transforms to apply to the one or more input images. If a computed score indicates color errors in the stitched image, the feedback module calculates and applies one or more photometric transforms to apply to the one or more input images.

Abstract: Provided are a damage diagram creation method, a damage diagram creation device, a damage diagram creation system, and a recording medium capable of detecting damage with high accuracy based on a plurality of images acquired by subjecting a subject to split imaging. In a damage diagram creation method, damage of a subject is detected from each image (each image in a state of being not composed) constituting a plurality of images (a plurality of images acquired by subjecting the subject to split imaging), and thus, damage detection performance is not deteriorated due to deterioration of image quality in an overlapping area. Therefore, it is possible to detect damage with high accuracy based on a plurality of images acquired by subjecting the subject to split imaging. Detection results for the respective images can be composed using a composition parameter calculated based on correspondence points between the images.

Abstract: An image processing apparatus that generates an image for character recognition from a read image includes at least one memory that stores instructions, and at least one processor that executes the instructions to perform extracting of an area of handwritten character information and an area of printed character information from the read image, clipping of a partial image of the area of handwritten character information and a partial image of the area of printed character information out of the read image, and generating of the image for character recognition by combining the partial image of the area of handwritten character information and the partial image of the area of printed character information being associated with each other.

Abstract: There is provided an image processing device and a method capable of suppressing lowering of image quality. Correction information that is information regarding correction of 3D data representing a three-dimensional structure constructed using 2D data representing a two-dimensional image is generated, and the generated correction information is coded. Furthermore, coded data of correction information that is information regarding correction of 3D data representing a three-dimensional structure constructed using 2D data representing a two-dimensional image is decoded, and 3D data is constructed using the 2D data and correction information generated by decoding coded data of the correction information. The present disclosure can be applied to, for example, an information processing device, an image processing device, an electronic apparatus, an information processing method, a program, or the like.

Abstract: Systems and methods for extracting information from a sheet of material to facilitate organization of information from paper, and other physical writing surfaces are provided. An example system includes a sheet of material and a device for scanning the sheet with an optical sensor. The sheet of material includes an indication region. The indication region allows for indictors to be marked corresponding with at least one a corresponding subregion to be extracted. The sheet of material further includes at least one fiducial mark for identifying a boundary of the sheet. The device includes a processor operably coupled to the optical sensor for causing the optical sensor to scan the sheet and detect a boundary thereof using the fiducial marks and further identify a designated subregion of the sheet. Upon identification of the designated subregion, the processor is configured to extract information contained in the designated subregion for organization of information.

Abstract: A method for searching an image database, comprising receiving an adulterated image of an object, the adulterated image including object annotations for visual reference, applying a first neural network to the adulterated image, correlating a result of the applying the first neural network with each image of a reference database of images, the result including an edited image of the object and each image of the reference database of images including a reference object, and selecting, as a matching image, at least one image of the reference database of images having correlation values above a threshold correlation value. The method may include applying a masking to the adulterated image. The masking may include performing, via a second neural network, object recognition on the adulterated image, applying, based on the object recognition, computer vision to detect callout features relative to bounding boxes, and generating a contour mask of the object.

Abstract: Disclosed herein is a method of identifying a line of a stave or a stem of a note in a digital image of a musical score comprising: converting the digital image into a matrix in which at least one cell of the matrix corresponds to a pixel of the digital image; setting the at least one cell of the matrix to a first value if the corresponding pixel of the digital image has a pixel intensity above a threshold intensity; identifying adjacent cells having the first value as linked cells, the adjacent cells corresponding to pixels being adjacent in one of a horizontal direction or a vertical direction of the digital image; identifying linked cells having a number of cells exceeding a threshold as a chain of cells; grouping adjacent chains of cells into a group of chains; determining a dimension of the group of chains; and comparing the dimension with a dimension threshold; wherein, if the dimension is above the dimension threshold, determining that pixels corresponding to linked cells of the group of chains corresp

Abstract: Dense depth information can be generated using only a monocular image and sparse depth information.

Abstract: A character restoration method and apparatus, a storage medium, and an electronic device are provided. The character restoration method includes: a character identifier of a character in a text region is determined, where the character identifier is used for uniquely identifying the character; and encoding is performed at least according to the character identifier, and encoded data is sent to a receiving end, where the encoded data is used for the receiving end to decode the encoded data and restore the character according to the character identifier obtained after decoding, that is, encoding is performed merely according to a small amount of information, and then the information is obtained by decoding, so as to restore the character.

Abstract: The present disclosure describes a method, system, and a computer readable medium for extracting tabular data present in a document. The method comprises detecting presence of at least one table in the document using a deep learning based model and a statistical method. The method further comprises identifying a type of the table based on determining a count of horizontal and vertical lines, presence of outer borders, and presence of row-column intersections in the table. The type of the table comprises a bordered table, a partially bordered table, or a borderless table. The method further comprises processing the detected table, depending on its type, to identify one or more cells present in the table. The method further comprises generating an output file by extracting the tabular data present in the table, where the extracting comprises performing optical character recognition on the identified one or more cells.