147 results about "Glyph" patented technology

An end-to-end rendering system enforces policy-constrained, symbolic presentation of artificial-intelligence (AI) outputs prior to any pixel emission. An AI accelerator emits inference tokens as (token identifier, confidence, domain tag) tuples into an output FIFO. A graphics processor with a command processor and SIMD co-processor executes a policy engine that runs a deterministic finite automaton (DFA) stored in non-transitory memory. The DFA consumes the tuples and produces, before any frame-buffer writes, a permit / deny decision and a visibility mask that constrain presentation attributes. A glyph selector maps permitted tuples to entries in a constrained glyph dictionary specifying a glyph identifier, semantic class, and allowed substitutions. A provenance tagger computes a cryptographic hash over at least the glyph identifier, a DFA-state policy identifier, a session nonce, and a checksum of the tuples to create an evidence capsule bound to the glyph. A device-aware renderer, consulting a device profile registry and a rendering grammar, emits a renderable asset for the glyph only when permitted by the visibility mask and grammar. A justification ledger records, for each displayed glyph, the evidence capsule and a monotonic timestamp. Executed entirely within the graphics processor, the pipeline prevents unauthorized tokens from entering the display path, enables cryptographically verifiable traceability of visible content, and reduces bandwidth by representing outputs as glyph identifiers rather than text or raster imagery, while allowing runtime policy updates without modifying the underlying inference model.

The invention belongs to the field of intelligent man-machine interaction, and relates to an intelligent writing and correcting method and system.The method comprises the steps that a flexible pressure sensor matrix and a coordinate positioning system are used for sensing multi-dimensional data generated when an input pen writes, and a four-dimensional writing feature space is constructed; a three-level correction system is adopted, and logical reasoning verification is conducted on the answers through a deep semantic understanding model; the three-stage correction system sequentially comprises OCR font matching, semantic correction based on a large language model and intelligent correction based on a process reward model; a cognitive diagnosis model is introduced, and the answer hesitation degree is judged by analyzing answer indexes; fusing question answering information, utilizing a large model to identify knowledge points to which questions belong, and inferring knowledge mastering weak points according to question answering conditions; writing information is accurately collected through an intelligent writing capture technology based on multi-modal sensing fusion, an intelligent correction integrated method is built in combination with a cognitive diagnosis model, and efficient recognition and accurate correction of written content are achieved.

The embodiment of the invention provides an image generation method and device, and the method comprises the steps: obtaining a wordart description text, a target content text and a condition image, and enabling the condition image to be used for constraining the font of a target wordart; based on the wordart description text, processing the condition image to generate a target wordart image corresponding to the condition image; and generating a target image corresponding to the target content text based on the target content text and the target wordart image. According to the method, perfect fusion of the wordart and the content is realized, the aesthetic property and expressive power of the image are improved, the creation threshold of the user is reduced, the image generation process is more efficient and intelligent, and diversified creative requirements are met.

This invention relates to the field of text processing technology, and in particular to a method, device, and medium for processing navigational notice text based on semantic enhancement. The method includes: first, acquiring a content carrier to be processed; then, acquiring the semantic vector and glyph feature vector of the content carrier; concatenating the two types of vectors to form an enhanced text representation; extracting temporal features from the enhanced text representation to obtain temporal features containing forward and backward logical relationships within the text; acquiring the weights of words and sentences in the temporal features and performing weighting to obtain weighted word representations and weighted sentence representations; performing correction processing on the weighted representations to generate corrected text; and finally, validating the corrected text and outputting the target text. This invention can improve the accuracy and efficiency of content carrier processing.

The invention belongs to the technical field of character pattern recognition, and particularly provides an oracle structure recognition method of a font pattern isomorphic network, which comprises three stages of font pattern structure feature extraction, font pattern isomorphic network model and oracle font structure recognition. Through oracle font skeleton extraction, oracle font skeleton singular point detection, skeleton burr and bifurcation optimization, and key point extraction as a node communication path as an edge, an oracle font graph structure is established, and graph structure nodes, edges and graph level features are calculated. The font graph isomorphic network integrates the advantages of a graph isomorphic network and dynamic edge and graph embedding, and learns vector representation of multi-level features such as nodes, edges and graphs of the oracle font graph structure so as to train and identify the font structure of the oracle. The method can be used for structure matching recognition of oracle character pattern images, has the advantage of being high in recognition accuracy, and is suitable for recognition of character pattern structures such as gold texts and seal scripts and recognition of social networks, biological information and molecular structures.

The invention discloses a stylized visual text editing method, a stylized visual text editing system, stylized visual text editing equipment and a storage medium, which are corresponding schemes, and the related schemes aim to solve the problem of style consistency existing in image text editing of an existing diffusion model, and the stylized visual text editing efficiency is improved by combining visual features of a font image and an input text image. The method comprises the following steps of: extracting style embedded information from a text image, and inputting the style embedded information as an enhanced style condition into a diffusion model to realize fine control on a diffusion process, so that the diffusion model can generate a text image with high readability and style consistency, and can realize maintenance of an original text style or style migration based on a reference image.

The invention provides a teaching document anti-copy protection method and system based on OCR interference resistance, and belongs to the technical field of information security and digital copyright protection. According to the method, anti-OCR font processing is applied to document characters, invisible disturbance symbols are inserted between characters or paragraphs, watermark information is embedded in document typesetting or font strokes, and finally a standard PDF or DOCX file is compiled. Watermark information is embedded through stroke thickness change, paragraph row spacing indentation perturbation and other modes. The system comprises a font disturbance module, a character disturbance module, a watermark embedding module, a compiling output module and a verification module. According to the method, the human eyes can normally read the document, but messy codes or disorder can occur when the OCR tool extracts the document, and the document cannot be directly reused; meanwhile, watermark information cannot be stripped, so that leakage tracking is facilitated; and the output file keeps a standard format and is compatible with the existing office teaching process. The method is suitable for anti-copying protection of teaching documents, scientific research data, test papers, contract files and the like.

The invention discloses a short message identification method and device, a nonvolatile storage medium and electronic equipment. The method comprises the following steps: acquiring a short message to be identified; a pre-trained short message classifier is adopted to perform feature extraction on the to-be-recognized short message to obtain multi-dimensional features, the multi-dimensional features at least comprise one of font features, pinyin features and semantic features, the font features are used for representing structures of characters in the to-be-recognized short message, the pinyin features are used for representing pronunciation of the characters in the recognized short message, and the semantic features are used for representing semantic features of the characters in the recognized short message; the semantic features are used for representing the meaning of the to-be-recognized short message; fusing the multi-dimensional features to obtain fused features; and identifying the fusion features by adopting a short message classifier to obtain the type of the short message to be identified. The technical problem that the short message recognition accuracy is low is solved.

The invention relates to the technical field of image detection, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a Chinese character font generation method, device, equipment and medium, the method comprises the following steps: obtaining a Chinese character image to be processed, and carrying out image coding on the Chinese character image to be processed to obtain a Chinese character image sequence; performing style feature extraction and semantic feature extraction on each Chinese character image vector in the Chinese character image sequence to obtain corresponding Chinese character style features and Chinese character semantic features; constructing a corresponding style loss function and a semantic loss function according to the Chinese character style features and the Chinese character semantic features; performing loss weighting calculation on the style loss function and the semantic loss function to obtain a target loss function; and performing font style generation on the to-be-processed Chinese character image according to the target loss function to obtain a target Chinese character font of the to-be-processed Chinese character image. The Chinese character font generation efficiency and font generation diversity can be improved.

Embodiments of the present disclosure provide a method, an apparatus and an electronic device for determining a word representation vector, and a computer-readable storage medium, which belong to a field of processing natural languages. The method includes obtaining a set of glyph units of a text; obtaining a context vector of the text based on the set of glyph units; and predicting next word of the text based on the context vector. The method for determining the word representation vector of the present disclosure can effectively obtain a corresponding set of glyph units even for hieroglyphics in which hyperbolic characters are prone to appear or languages evolved from the hieroglyphics, thereby improving an accuracy of determining the word representation vector.

The invention discloses a ViT-based automatic detection and recognition system and method for Manchu ancient book characters, and belongs to the technical field of artificial intelligence and digital literature protection. The system comprises a YOLO target detection module, a positioning network module, a ViT module and a classifier module. The YOLO target detection module is used for identifying and positioning each individual character area in the whole Manchu ancient book image, the positioning network module is used for automatically adjusting the position, the rotation angle and the scaling of the character image, and the ViT module is used for extracting the deep feature of the character image and modeling the character visual representation. And the classifier module is used for mapping the feature vectors output by the ViT module into specific character tags and splicing the specific character tags into a transcription text. The invention provides an end-to-end intelligent processing system, solves the problems of character pattern diversity, image noise, multi-language mixing and the like of Manchu literatures, and realizes high-precision identification of Manchu characters and intelligent sorting and translation of Manchu and Chinese bilingual literatures.

Methods, system, and apparatus, including computer programs encoded on a computer storage medium. for generating fonts. In one aspect. a method comprises generating glyphs for one or more fonts using an adaptive refiner model.

The invention relates to the technical field of writing error recognition, and discloses a Chinese writing error intelligent recognition method and system based on a deep neural network, and the method comprises the following steps: 1, obtaining a target single Chinese character image after binarization processing, and obtaining a normalized binary font image; 2, skeleton extraction and node labeling are carried out on the normalized image, and a font topological graph is constructed; 3, determining a structure normal form label based on the topological graph and image projection, and dividing parts to obtain an outer surrounding region, an inner part region, left and right parts and intersection information; step 4, calculating consistency measurement of surrounding, left-right and cross structures; step 5, obtaining a corresponding standard measure in combination with the standard font of the target Chinese character, setting a fixed tolerance to form a standard parameter interval, and generating a structural feature vector; and step 6, outputting a writing error recognition result according to the deep neural network model. According to the invention, automatic identification and error type determination of Chinese writing structural errors are realized.

The invention relates to the technical field of artificial intelligence, can be applied to the medical field and the financial science and technology field, and discloses a font generation method and device based on a tensor high-order coupling layer, equipment and a medium, which are applied to a dynamic financial document generation system or an automatic labeling scene of a medical image report. The method comprises the following steps: acquiring font style descriptors and font structure data, and preprocessing the font style descriptors and the font structure data to generate standardized font style descriptors and font structure embedding; performing feature extraction and dynamic parameter generation processing on the standardized style descriptors to generate style factors; obtaining a data segmentation vector, and performing multi-rank tensor decomposition on the data segmentation vector based on the style factor to obtain a transformation feature; adjusting the coupling strength between different attributes of the transformation features to generate features after gating optimization; and embedding the gated optimized features and the font structure for feature fusion and feature decoding to generate a target font image. The method has the advantages that the generated fonts are high in visual quality and rich in style diversity.

The invention relates to the technical field of intelligent decision making, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a character font generation method, device, equipment and medium based on feature extraction. Obtaining font initial features; performing multi-level feature refinement processing on the font initial features to obtain font refinement features; performing style consistency processing on the font refinement features to obtain style consistency features; calculating predicted fonts according to the style uniformization features, and calculating a multi-dimensional loss function of the character font data set according to the predicted fonts; and performing parameter optimization on the pre-constructed font generation model according to the multi-dimensional loss function to obtain a target font generation model, and performing font generation by using the target font generation model.

The invention relates to the technical field of content extraction, in particular to a multi-modal hybrid document OCR (Optical Character Recognition) and structured extraction method, which comprises the following steps of: acquiring an image text region bounding box and classifying a style, extracting a font or stroke sequence to generate a character positioning structure, dividing paragraph and sentence groups to classify semantic fields, and calculating a field matching relationship to generate structural mapping. According to the method, logic mapping is constructed through character two-dimensional coordinate sorting and paragraph contours, complete reconstruction of a page structure is enhanced, semantic field categories are extracted by using syntactic density of sentence paragraph division and inter-paragraph features, the accuracy of field classification is improved, and the method has the advantages of being simple in structure, convenient to operate and high in practicability. A field mapping relation is established through Jaccard similarity and part-of-speech consistency analysis between a head word and a standard field keyword, a field path index and a structure node link are clarified, field semantic affiliation and structure position output are unified, and the document structure reduction degree and field extraction accuracy are improved.

Apparatus and methods for merging embedded fonts. In an embodiment, an apparatus is configured to identify embedded fonts in a plurality of electronic files, identify glyphs represented in the embedded fonts, generate a synthesized font subset comprising a union of the glyphs found in the embedded fonts, and assign glyph code points to the glyphs of the synthesized font subset.

The invention relates to an AdobeAudition (AU) extension program-based automatic track matching system and method, and relates to the technical field of audio processing, a picture book analysis module identifies and analyzes a role line sequence and an interval parameter of a line book through a regular expression and a role tag; the audio matching and loading module is used for matching role audios according to a filename rule or a metadata label and loading the role audios to an initial track; the silence detection and marking module adds a mark at a non-silence initial position by adopting framing energy calculation; the line-audio verification module is used for realizing audio and line matching degree analysis through voice recognition to text and font pinyin double-path similarity calculation, and providing a visual calibration interface; and the automatic execution module supports a full-automatic sequential splicing mode or a semi-active sentence-by-sentence splicing mode. The method comprises the steps of line book analysis, audio matching and loading, mute detection marking, verification and calibration and dual-mode execution. The problems of low manual rail alignment efficiency and poor precision in the audio book making process are solved.

The invention discloses an interactive Chinese character traceability and writing correction system, and belongs to the technical field of Chinese character education. Aiming at the problems of traceability staticization, correction simplification and path solidification of an existing tool, the technical scheme comprises the following steps: constructing a database of seven types of font evolution from oracle to regular script, and dynamically displaying font evolution by combining 3D modeling and AR rendering; multi-mode writing data are collected through a pressure sensing pen, an infrared camera and the like, and the AI model is corrected in real time from pressure, posture and structure dimensions; and on the basis of the user error type, related Chinese character traceability content is pushed by reinforcement learning and stepped practice is carried out, so that personalized path optimization is realized. The system can improve Chinese character meaning understanding depth, writing normalization and learning efficiency, is adaptive to scenes of basic education, calligraphy training and the like, and promotes Chinese character learning to be converted from passive cognition to active construction.

The invention relates to the technical field of computer data processing, in particular to a multi-language display method and system and wearable intelligent equipment. The method comprises the following steps: segmenting the content of a display text based on language types of various font sub-files cached in advance; all the segments are reset based on a typesetting engine, font contour information of all the characters is output, and the font contour information comprises deformation and connected characters; typesetting information is determined on the basis of line width limitation of the lightweight general graphics library, and the typesetting information comprises line tail broken lines, word spacing and self-adaptive zooming; and based on the typesetting information and the font contour information of all the characters, selecting a dot matrix font drawing mode / vector font drawing mode for rendering. By means of the method, multi-language compatibility can be achieved, and meanwhile the problems of line breaking errors, character pattern dislocation or extremely low rendering speed and the like occurring when mixed text rendering is processed are solved.

The application relates to the technical field of natural language, and discloses a text error correction processing method, which comprises the following steps: obtaining a text to be corrected; performing feature extraction on the text to be corrected through a feature layer of a text error correction model to obtain position features, image features and font features; performing error labeling on text characters in the text to be corrected according to the position features, the image features and the font features through a labeling layer of the text error correction model to obtain error characters; performing stroke decomposition on each error character to obtain character strokes; performing character matching on the character strokes of each error character through a preset homophone dictionary to obtain candidate characters; screening target characters from all the candidate characters, and replacing the error characters with the target characters to obtain a target text. Through the character matching on the character strokes of each error character, the character matching using stroke information is realized, and the accuracy of text error correction in the information input process in the insurance field is improved.

The application provides an OCR text correction method and device. A correct probability of a Chinese character at each position in to-be-corrected text is obtained. A character shape structure word embedding vector of the Chinese character at each position in the to-be-corrected text is obtained. An input word embedding vector of the Chinese character at each position is calculated according to the word embedding vector corresponding to the Chinese character at each position in the to-be-corrected text, the correct probability and the character shape structure word embedding vector, and an input word embedding vector set is formed. The input word embedding vector set is input into a second encoder to form a coded input word embedding multi-dimensional vector. The coded input word embedding multi-dimensional vector is input into a correction layer to obtain corrected text. The correction layer is provided with a correction neural network formed by training of a Chinese corpus. The OCR text correction method and device provided by the application no longer selects a candidate word from an existing confusion set for correction, reduces the occurrence of missing words, and improves the accuracy of correction.

The present application relates to the technical field of computer information retrieval, and particularly relates to a digital publishing platform supplementary character retrieval method and system, the present application provides a kind of digital publishing platform supplementary character retrieval method and system, retrieve function is called out by user end, supplementary character feature is matched with supplementary character database, corresponding glyph is extracted according to matching data, after obtaining search term, the search term data uploaded to central server is processed by indexing word division data in supplementary character database and preset algorithm based on supplementary character, key word full-text retrieval is carried out by word division, and the search result is displayed in user end, solve the supplementary character of prior art and can only be expressed by screenshot form, picture is difficult to form effective index, cannot be directly added to full-text retrieval engine, leading to related digital publishing application cannot be based on supplementary character to realize key word retrieval, pinyin, initial letter retrieval and other problems.

The invention discloses a printed text content display method and device based on cross-platform consistency, and the method comprises the steps: obtaining a to-be-printed character string and a defined text object description protocol, and obtaining a text attribute structure according to the defined text object description protocol; obtaining the resolution ratio of the ink-jet printer nozzle, and enabling the resolution ratio of the PC upper computer to be consistent with the resolution ratio of the ink-jet printer nozzle according to the resolution ratio of the ink-jet printer nozzle; adopting a text shaping engine to obtain corresponding font list information according to the text attribute structure; adopting a font rasterization engine to obtain corresponding font contour information according to the font list information and the text attribute structure; obtaining the pixel width and height of the whole line of text according to the font list information and the font contour information; according to the obtained font list information, font contour information and resolution parameters, drawing to a display screen by adopting a Skia rendering engine; therefore, cross-platform measurement and drawing consistency of the text content of the ink-jet printer is realized.

The invention discloses a printing control method and electronic equipment. The method comprises the following steps: acquiring to-be-printed data; the coding type and the language type of the to-be-printed data are analyzed; selecting word stock processing channels based on the coding type and the language type, wherein the word stock processing channels comprise a dot matrix word stock processing channel and a vector word stock processing channel containing an integer rendering process; the to-be-printed data is converted into printing dot matrix data through the word stock processing channel; printing is completed based on the printing dot matrix data. According to the method, by establishing a dot matrix and vector mixed font library processing architecture and based on coding and language type intelligent routing, the problems of font deformation and stacking display of a complex language family are solved by utilizing a shaping rendering engine while high-speed printing of basic characters is guaranteed, and the balance of the printing speed and the output quality in a resource limited environment is realized.

The present disclosure relates to a font recognition method, device, readable medium and electronic equipment. The font recognition method divides the image to be recognized into a plurality of sub-images through the predetermined font recognition model, and obtains the first image corresponding to each sub-image. Image features, determine the second image features corresponding to the image to be recognized based on the first image features corresponding to each sub-image of the image to be recognized, the second image features include each sub-image of the image to be recognized and the context-related features of other sub-images are used to determine the font type corresponding to the target text based on the second image features. In this way, the image to be recognized can be described more comprehensively and accurately based on the correlation between each word image and other sub-images. This can effectively improve the accuracy of font recognition results and also effectively improve the font recognition rate.

This application discloses a method and apparatus for calligraphy and painting recognition based on deep learning, belonging to the field of artificial intelligence and digital image processing technology. The method includes: acquiring images of calligraphy and painting works; preprocessing and enhancing restoration by introducing a generative adversarial network with an edge-preserving loss function to preserve the texture of the ink marks; extracting the character structure features of the signature, inscription, and seal areas; inputting them into a specially trained optical character recognition and semantic analysis hybrid model; during decoding, weighted fusion of visual feature vectors and contextual semantic probability vectors to output initial recognition text; combining a calligraphy dictionary database, performing semantic error correction and matching through a joint calculation formula of quantified character topological edit distance and semantic probability to obtain and output the target recognition text. This solves the problems of failure due to lack of topological repair capability for damaged pixels and inability to hit the correct characters, achieving high-precision recognition and deep knowledge interpretation of calligraphy and painting text.

The invention relates to a font matching method and device and a storage medium, and the method comprises the steps: obtaining a source font corresponding to a target character in a text presented by a source font, and rendering the source font into a source font image; extracting a source font feature corresponding to the source font image; obtaining a candidate font feature corresponding to any candidate font image; wherein the candidate font images are font images corresponding to candidate fonts in candidate fonts; and determining a target font matched with the text from all the candidate fonts according to the source font feature and any candidate font feature. Therefore, the font matching is carried out based on the font characteristics, and the font matching task is not converted into the image classification task, so that the problems that the classification result is wrong and the font matching accuracy is influenced when the font quantities of different fonts are different can be avoided.

This application discloses a method, apparatus, electronic device, and storage medium for character stroke extraction. The method includes: acquiring the glyph curve of the character to be processed; performing discrete sampling on the glyph curve to obtain a discrete point set; selecting at least two stroke key points from the discrete point set to obtain a closed curve containing at least two stroke key points, thereby obtaining the character strokes. Through the above method, this application can improve the speed and accuracy of character stroke extraction.

The invention relates to the technical field of medical big data analysis, in particular to a multi-individual accurate correspondence method and system based on medical element association backstepping. According to the method, initial data are refined into two types of variable quantity and constant quantity, and data integrity and correctness checking is completed by performing font checking on constant quantity'fixed characters' and performing quantity checking on variable quantity'variable factors'; a checking and checking mode of four-layer nesting, mutual quality verification and layer-by-layer progressive is applied, correct input of fonts of'fixed characters' is guaranteed through two-round input character checking, correct input of the number of'variable factors' is guaranteed through two-round logic relation checking, logicality is good, the operation speed is high, and the processing efficiency is high. Through a three-layer traversal loop nesting mode, screening correspondence of a main screening field individual and other font field individuals is completed, a complex and tedious screening comparison function is achieved through a simple and efficient function code, and the problems that a function formula of a traditional method is tedious and long, and integration and expansibility are poor are solved.