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公开(公告)号：US20250005951A1
公开(公告)日：2025-01-02
申请号：US18416699
申请日：2024-01-18
Applicant: Smart Engines Service, LLC
IPC: G06V30/414 , G06K7/14 , G06T7/73 , G06V30/16 , G06V30/186 , G06V30/19
Abstract: A method for locating machine-readable zones in document images based on feature points is disclosed. In an embodiment, feature points are found in the image, and linear objects are located in the image (e.g., by applying a Fast Hough Transform to the image). The feature points are filtered based on their correspondence to the linear objects. The filtered feature points are grouped into clusters, and rectangular zones are defined around each cluster. A final rectangular zone is selected from the defined rectangular zones. This method of locating machine-readable zones is designed to meet the requirements for real-time operation on mobile devices.
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公开(公告)号：US20230245320A1
公开(公告)日：2023-08-03
申请号：US18123737
申请日：2023-03-20
Applicant: Smart Engines Service, LLC
Inventor： Alexander Vladimirovich SHESHKUS , Dmitry Petrovich NIKOLAEV , Vladimir L`vovich ARLAZAROV , Vladimir Viktorovich ARLAZAROV
IPC: G06T7/168 , G06N3/0464 , G06N3/048 , G06N3/09
CPC classification number: G06T7/168 , G06N3/09 , G06N3/048 , G06N3/0464 , G06T2207/20021 , G06T2207/20061 , G06T2207/20081 , G06T2207/20084 , G06T2207/30256
Abstract: Artificial intelligence using convolutional neural network with Hough Transform. In an embodiment, a convolutional neural network (CNN) comprises convolution layers, a Hough Transform (HT) layer, and a Transposed Hough Transform (THT) layer, arranged such that at least one convolution layer precedes the HT layer, at least one convolution layer is between the HT and THT layers, and at least one convolution layer follows the THT layer. The HT layer converts its input from a first space into a second space, and the THT layer converts its input from the second space into the first space. The CNN may be applied to an input image to perform semantic image segmentation, so as to produce an output image representing a result of the semantic image segmentation.
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公开(公告)号：US20230093474A1
公开(公告)日：2023-03-23
申请号：US17989819
申请日：2022-11-18
Applicant: Smart Engines Service, LLC
Inventor： Natalya Sergeevna SKORYUKINA , Vladimir Viktorovich ARLAZAROV , Dmitry Petrovich NIKOLAEV , Igor Aleksandrovich FARADJEV
IPC: G06V30/413 , G06K9/62 , G06V10/40 , G06V10/75 , G06V10/44 , G06V30/418
Abstract: Efficient location and identification of documents in images. In an embodiment, at least one quadrangle is extracted from an image based on line(s) extracted from the image. Parameter(s) are determined from the quadrangle(s), and keypoints are extracted from the image based on the parameter(s). Input descriptors are calculated for the keypoints and used to match the keypoints to reference keypoints, to identify classification candidate(s) that represent a template image of a type of document. The type of document and distortion parameter(s) are determined based on the classification candidate(s).
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公开(公告)号：US20220067363A1
公开(公告)日：2022-03-03
申请号：US17237596
申请日：2021-04-22
Applicant: Smart Engines Service, LLC
Inventor： Natalya Sergeevna SKORYUKINA , Vladimir Viktorovich ARLAZAROV , Dmitry Petrovich NIKOLAEV , Igor Aleksandrovich FARADJEV
Abstract: Efficient location and identification of documents in images. In an embodiment, at least one quadrangle is extracted from an image based on line(s) extracted from the image. Parameter(s) are determined from the quadrangle(s), and keypoints are extracted from the image based on the parameter(s). Input descriptors are calculated for the keypoints and used to match the keypoints to reference keypoints, to identify classification candidate(s) that represent a template image of a type of document. The type of document and distortion parameter(s) are determined based on the classification candidate(s).
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公开(公告)号：US20250037492A1
公开(公告)日：2025-01-30
申请号：US18592067
申请日：2024-02-29
Applicant: Smart Engines Service, LLC
Inventor： Natalya Sergeevna SKORYUKINA , Vladimir Viktorovich ARLAZAROV , Dmitry Petrovich NIKOLAEV , Igor Aleksandrovich FARADJEV
IPC: G06V30/413 , G06V10/40 , G06V10/44 , G06V10/75 , G06V30/10 , G06V30/418
Abstract: Efficient location and identification of documents in images. In an embodiment, at least one quadrangle is extracted from an image based on line(s) extracted from the image. Parameter(s) are determined from the quadrangle(s), and keypoints are extracted from the image based on the parameter(s). Input descriptors are calculated for the keypoints and used to match the keypoints to reference keypoints, to identify classification candidate(s) that represent a template image of a type of document. The type of document and distortion parameter(s) are determined based on the classification candidate(s).
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Patent Agency Ranking
6.发明公开公开(公告)号：US20240354917A1
公开(公告)日：2024-10-24
申请号：US18137181
申请日：2023-04-20
Applicant: Smart Engines Service, LLC
Inventor： Vladimir Viktorovich ARLAZAROV , Dmitrij Petrovich NIKOLAEV , Dmitrij Valerevich POLEVOJ , Dmitrij Gennadievich SLUGIN , Irina Andreevna KUNINA , Irina Vitalievna SIGAREVA
CPC classification number: G06T7/0002 , G06V10/25 , G06V10/54 , G06V10/60 , G06V10/761 , G06T2207/20036 , G06T2207/20061 , G06T2207/30176
Abstract: The present disclosure relates to computer technology for document security and authentication. Embodiments increase the accuracy and reliability of detecting (recognizing) the fact that a digital copy of a document has been presented in the form of a screen capture. An input image of a document, with known boundaries and internal structure, is received. Independent analysis of the specified areas of the document image is performed for certain anomalies that may occur from screen capture. When at least one of the anomalies is detected, the input image may be determined to be a digital copy instead of a physical document. The anomalies may be divided by the type of analyzed areas: analysis of the entire image of the document inside the localized boundaries; analysis of the image of the document boundaries; and/or a document area selected in accordance with the document's known structure.
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7.发明公开公开(公告)号：US20240054180A1
公开(公告)日：2024-02-15
申请号：US18210395
申请日：2023-06-15
Applicant: Smart Engines Service, LLC
Inventor： Anton Vsevolodovich TRUSOV , Elena Evgenyevna LIMONOVA , Dmitry Petrovich NIKOLAEV , Vladimir Viktorovich ARLAZAROV
Abstract: No computationally efficient CPU-oriented algorithms of ternary and ternary-binary convolution and/or matrix multiplication are available. Accordingly, a microkernel is disclosed for high-performance matrix multiplication of binary, ternary, and ternary-binary matrices for central processing units (CPUs) with the Advanced Reduced Instruction Set Computer (RISC) Machine (ARM) v8 architecture.
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公开(公告)号：US20230137300A1
公开(公告)日：2023-05-04
申请号：US17980029
申请日：2022-11-03
Applicant: Smart Engines Service, LLC
Inventor： Daniil Vyacheslavovich TROPIN , Aleksandr Mikhailovich ERSHOV , Dmitry Petrovich NIKOLAEV , Vladimir Viktorovich ARLAZAROV
Abstract: Advanced Hough-Based On-Device Document Localization. In an embodiment, lines are detected in an input image of a document. The lines are searched for candidate quadrilaterals. For at least a subset of the found candidate quadrilaterals, a contour score is calculated, and the candidate quadrilaterals are saved or discarded based on their contour scores. For each saved candidate quadrilateral, a contrast score is calculated. A final candidate quadrilateral is selected, based on the combined contour and contrast scores for the saved candidate quadrilaterals, to represent the borders of the document.
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公开(公告)号：US20220020185A1
公开(公告)日：2022-01-20
申请号：US17180397
申请日：2021-02-19
Applicant: Smart Engines Service, LLC
Inventor： Konstantin Bulatovich BULATOV , Marina Valerievna CHUKALINA , Alexey Vladimirovich BUZMAKOV , Dmitry Petrovich NIKOLAEV , Vladimir Viktorovich ARLAZAROV
Abstract: A system for monitored tomographic reconstruction, comprising: an x-ray generator configure to generate x-ray beams for scanning an object; detectors configured to capture a plurality of projections for each scan; at least one hardware processor; and one or more software modules that, when executed by the at least one hardware processor, receive the plurality of projections from the detectors and as each of the plurality of projections is received, generate a partial reconstruction, and make a stopping decision with respect to whether or not another projection should be obtained based on a stopping problem and that defines when a reconstructed image quality is sufficient with respect to the expended cost as determined by a stopping rule.
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公开(公告)号：US20240257491A1
公开(公告)日：2024-08-01
申请号：US18409675
申请日：2024-01-10
Applicant: SMART ENGINES SERVICE, LLC
CPC classification number: G06V10/443 , G06V10/28 , G06V10/34
Abstract: The computation of local feature descriptors for image matching in computer vision can be computationally expensive for real-time on-device applications. Accordingly, disclosed embodiments speed up such computations by precomputing values for gradient maps, and storing them in lookup tables indexed by partial derivatives. In addition, certain embodiments introduce global smoothing, and optionally, global gradient maps. In an embodiment that eliminates all floating-point operations, arctangents can be precomputed for a fixed number of angles, and quantization can be performed when computing the local feature descriptors.
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