19 results about "Stroke order" patented technology

The invention discloses a system and a device for identifying names of other people selected from elected handwritten Chinese characters, and belongs to the field of identification, and the method comprises the following steps: analyzing a time dependency relationship of a stroke sequence by adopting a recurrent neural network, and combining a predefined Chinese character stroke sequence rule to obtain a preliminary Chinese character candidate set; for the weighted Chinese character candidate sequence, if the highest confidence is lower than a preset threshold value, analyzing the semantic matching reasonability of the weighted Chinese character candidate sequence through a pre-trained language model to obtain an optimized Chinese character candidate sequence; according to the optimized Chinese character candidate sequence, a sequence matching algorithm is adopted to calculate the similarity between the optimized Chinese character candidate sequence and names in a name database, and a preliminary name candidate set is obtained; and for the final name candidate set, adopting a multi-modal verification algorithm, fusing the repaired stroke feature vector and semantic matching reasonability, determining the confidence coefficient of the final name candidate set, and obtaining a confirmed name record.

The present application belongs to the field of computer vision and vector image generation, and particularly relates to a vectorized Chinese character pattern generation method based on a large model. The method comprises the following steps: step one, data preprocessing; step two, stroke feature extraction; step three, feature vector discretization coding; step four, stroke sequence combination; step five, feature coding prediction; step six, coding feature restoration; and step seven, stroke restoration. The present method combines Chinese character stroke order information, and on the basis of being able to complete Chinese character stroke generation to form a complete vector image, can also generate continuous semantic Chinese character vector text content in the form of continuously predicting the next character stroke, can complete missing character shapes in the case of incomplete font library, realize creative vectorized Chinese character text generation, make contributions to the fields of artistic character shape generation, Chinese character font auxiliary design, advertisement text design, etc., reduce labor costs, and realize efficient generation.

The application discloses a Chinese character sorting, searching and dictionary constructing method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: obtaining a first character of a Chinese character as a first character according to a stroke order, and encoding the first character to obtain a first character code, wherein the first character comprises a first character component which can be independently formed into a character and cannot be split, and a first main stroke component of the Chinese character which does not comprise any character component; obtaining the number of strokes included in each Chinese character, and obtaining a stroke string corresponding to each Chinese character according to a preset stroke character coding rule; sorting the Chinese characters by taking the first character code as a first sorting field, the number of strokes as a second sorting field, and the stroke string as a third sorting field, wherein the first sorting field has the highest priority, and the third sorting field has the lowest priority. The embodiment can solve the problems of sorting and searching difficulties caused by the definition and position of the component.

Systems or methods for presenting or generating an animated realization of one or more letter glyphs based on progressively exposing a continuous mapping of brush head shapes following a letterform stroke order. A machine-learning model is used to generate animation metadata from the one or more letter glyphs. The animation metadata including a centerline, the continuous mapping of brush head shapes that is used to sweep along the centerline, and the letterform stroke order to generate the animated realization of the one or more letter glyphs.

The application discloses a method and a terminal for automatically generating handwriting Chinese character animation, obtains a target Chinese character for which handwriting Chinese character animation is to be generated, analyzes each stroke of the target Chinese character and corresponding stroke type and center point data of the stroke; determines corresponding vertex data according to the stroke type of the stroke; calculates connection data required for drawing the stroke according to the center point data and the vertex data corresponding to the stroke; generates handwriting stroke animation of the corresponding stroke according to the connection data, integrates handwriting stroke animation corresponding to each stroke according to the stroke order of the target Chinese character, and obtains handwriting Chinese character animation of the target Chinese character. The application can automatically generate handwriting Chinese character animation according to the requirements of a user, simulate a real writing process during generation, improve the interactive experience of the user, and save manpower and resources.

This invention discloses an automatic pattern-making method for Chinese character embroidery based on the fusion of semantic-driven and process-constrained approaches, solving the problems of unreasonable stitch distribution, severe path redundancy, and difficulty in balancing semantic structure and physical manufacturing constraints in existing automatic embroidery pattern-making technologies. The method includes: acquiring unstructured Chinese character images; performing target detection and semantic recognition on the Chinese character regions to generate structured semantic labels; introducing standard stroke order templates based on the semantic labels and decoupling the topological structure of the Chinese characters through deformation registration to obtain single-stroke processing units arranged in the writing order; performing geometric modeling on the single strokes, extracting the central axis, and reconstructing continuous boundaries; performing topological partitioning of complex stroke regions based on pivot decomposition to generate sub-regions suitable for embroidery processing; generating adaptive stitch paths within the sub-regions and optimizing the paths; and finally quantizing and encoding the stitch trajectories to generate processing instruction files that can be executed by embroidery equipment.

The present application relates to a method and system for intelligent assessment of Chinese character writing ability, comprising the following steps: when a recognition start command is received, writing data sent by a writing recognition terminal is received in real time; the writing data is sent to a writing analysis model, the writing analysis model compares the stroke order data of the Chinese character text with pre-stored standard stroke order information, and outputs a stroke order comparison result; the stroke order comparison result includes correct stroke order information and incorrect stroke order information; the Chinese character text is compared with a preset standard text for contour similarity, and a comparison score is output; if incorrect stroke order information exists, the Chinese character text associated with the incorrect stroke order information is screened out, and the standard stroke order information corresponding to the Chinese character text is associated with the Chinese character text to generate a stroke order correction data packet; the comparison score and the stroke order correction data packet of the Chinese character text are sent to the writing recognition terminal. The present application has the effect of facilitating the judgment of the correctness of each student's writing stroke order.

The invention discloses an intelligent anti-shake pen based on vector force guidance and a writing method, and the intelligent anti-shake pen comprises a pen body housing, an internal core support, a slidable writing refill assembly, a tremor suppression module, a vector force stroke auxiliary driving module, a bidirectional interaction module and a main controller. The tremor suppression module monitors the tremor transmitted to the pen body due to the tremor of the hand of a user in real time through a built-in inertial measurement unit and drives the reverse micro-vibration assembly to generate dynamically matched compensation torque, and meanwhile, the vector force stroke auxiliary driving module outputs the compensation torque to the pen body according to a stroke instruction issued by an external intelligent terminal. Physical guiding force which is controllable in direction in the two-dimensional writing plane is applied to the writing refill assembly. And the main controller cooperatively regulates and controls anti-shake and guide, and performs closed-loop communication with an external terminal through the bidirectional interaction module. According to the invention, active anti-shake and active stroke guide functions are combined, so that a hand tremor patient can be effectively helped to write stably, a writing learner is assisted to master a correct stroke order, and the writing stability and accuracy are remarkably improved.

The invention mainly relates to the technical field of software development, and provides a method and system for drawing Chinese characters based on a Qt platform in order to improve the visualization degree of a Chinese character writing rule in a Chinese character teaching scene, and the method and system are characterized in that the Qt platform loads character contour data and stroke node data of corresponding Chinese characters according to target Chinese characters input by a user; fitting Chinese character contours based on the character contour data; according to the method, the filling spacing is calculated based on the stroke node data, and color filling is performed on the interiors of the Chinese character contours according to the calculated filling spacing, so that cross-platform visual consistency during Chinese character writing is ensured, dependence on a system font engine is eliminated, and advanced teaching functions such as stroke order animation, interaction highlight and radical decomposition are endowed to a Chinese character display unit.

The invention provides an online handwriting stroke order feature construction method and system and a handwriting identification method, and the method comprises the steps: analyzing handwriting collection data (x, y, p, t, s), and segmenting the handwriting into a plurality of strokes by using a point with a speed v close to 0 as a segmentation point; constructing a stroke order feature S including a stroke order feature, a stroke angle feature, a stroke type feature, a stroke length feature, a stroke position feature and a stroke conversion feature; and processing the stroke order feature S through frequency mapping transformation, extracting a high-frequency spectrum component in the stroke order feature S by using a high-frequency oscillation primary function in the frequency mapping transformation, and converting the stroke order feature S into a representation form suitable for a deep learning model. The method not only can reflect the sequence of strokes, but also can reflect the space structure difference caused by the sequence of strokes, remarkably improves the problem that a deep learning model is insensitive to different stroke orders, and improves the performance and generalization ability of the model.

The invention discloses a concave finger mark stroke literacy and calligraphy practicing card and a method thereof, belongs to the technical field of Chinese character literacy and calligraphy practicing auxiliary tools, and solves the technical problems that an existing calligraphy practicing tool lacks finger transition practicing, literacy and calligraphy practicing are separated, and adaptability is poor. According to the calligraphy practicing card, a hard material serves as a base material, the base material is provided with matts, stroke pits simulating finger writing traces are formed in the matts, auxiliary character learning information such as syllables and stroke orders is printed, and the card body size and content can be customized according to different crowds; according to the matched calligraphy practicing method, muscle memory formed by finger depicting and sinking serves as the core, and seamless connection from finger depicting to pen writing is achieved through the steps of card selection, depicting, character learning, pen writing transition and the like. The device is low in manufacturing cost, can effectively standardize the hand writing track, reduces the calligraphy practicing difficulty, achieves the synchronization of character learning and calligraphy practicing, is suitable for children, students, foreigners and other groups, is easy to popularize in batches, and greatly improves the Chinese character learning and writing practicing efficiency.

The invention relates to the technical field of Chinese character teaching, in particular to a Chinese character writing stroke order real-time error correction system and method based on deep learning, and the system comprises a preprocessing module, a multi-scale space-time convolution network module, a stroke order error diagnosis module and a correction feedback module. The multi-scale space-time convolutional network module extracts space-time features through a double-flow heterogeneous architecture, constructs a feature pyramid, and enhances key features by applying a dynamic attention mechanism, and the stroke order error diagnosis module analyzes stroke order features based on a rule base, detects multiple error types through multi-task learning, and determines the stroke order error. According to the system, 42 stroke order errors can be accurately recognized, targeted feedback is provided, and Chinese character writing teaching is effectively assisted.

The present disclosure relates to a stroke detection method and device, readable medium and electronic equipment. The method comprises: obtaining inputted to-be-recognized strokes in a user writing a target character, the target character being composed of at least two standard strokes; determining a similarity between the to-be-recognized strokes and a target standard stroke as a first similarity probability, the target standard stroke being at least one of the standard strokes; determining a probability that the to-be-recognized strokes are the target standard strokes as a second similarity probability according to input content before the to-be-recognized strokes; and determining whether a stroke order of writing the to-be-recognized strokes is correct according to the first similarity probability and the second similarity probability. Thus, the accuracy of stroke detection can be effectively improved, the efficiency of stroke detection can be improved, and real-time detection can be realized during user writing.

The present invention relates to computer technology, and specifically to a method for identifying illegal advertisements that combines text visual features and text content features. The method utilizes three methods to convert a color image into three features: the text visual image itself, the text visual image stroke features, and the image text recognition into text features. VGG16 is used to extract image features. RAN is used to extract the stroke order features of Chinese characters. A CNN-encoder / decoder architecture is used to extract the stroke features of Chinese characters and then embeds and transforms them into image features. DenseNet is used for feature learning and classification. Optical Character Recognition (OCR) is used to convert the text portion of an image into text information. Rule matching and review are performed on the text information. A RoFormer neural network model is used to perform feature learning and splitting on sentence-level text information. The method then identifies illegal advertisements. This method can provide strong support for the advertising review and supervision systems of major website platforms.

The application discloses a method and a terminal for generating a handwriting Chinese character animation quickly, acquires a target Chinese character for which a handwriting Chinese character animation is to be generated, selects matching data corresponding to the target Chinese character in a Chinese character database, generates a connecting point set of each stroke including a starting vertex and an ending vertex according to the matching data, applies a connecting line matching rule to the connecting points in the connecting point set for connecting line matching to generate connecting line data of the corresponding stroke, and generates a handwriting Chinese character animation of the target Chinese character according to stroke orders of all strokes of the target Chinese character and the connecting line data. The application can acquire connecting line related information corresponding to the target Chinese character more accurately and quickly based on data matching, generates connecting line data of each stroke in real time, simulates real handwriting, realizes strokes of Chinese characters appearing one by one, helps learners to understand and practice Chinese character writing better, has a more real and vivid experience, saves storage space, and is not limited by storage or performance.

The invention provides a handwritten Chinese character stroke order recognition method based on a semantic segmentation model, and the method comprises the steps: converting handwritten sequence data into a handwritten Chinese character path grayscale image Ih, and converting printed sequence data into a printed path grayscale image Ip; predicting a spliced image of a handwritten Chinese character path gray level image Ih and a printed form path gray level image Ip by using a semantic segmentation model, wherein the model takes a dual-channel gray level image as input; generating a mask pattern of each standard stroke according to the printing body sequence data; calculating an average gray value of each standard stroke mask image on the spliced image predicted by the model; and sorting the average gray values of all the standard strokes so as to determine a stroke writing sequence and realize stroke order identification. By applying the technical scheme of the invention, the problem of difficulty in accurately and efficiently identifying the stroke order of handwritten Chinese characters with various writing styles and non-standard stroke orders in the prior art can be effectively solved.

The application discloses a writing evaluation method, device and equipment, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring stroke data of a to-be-tested font in real time; for a pre-set stroke order evaluation dimension, determining the difference between each to-be-tested stroke of the to-be-tested font and each standard stroke of a standard font according to the stroke data of the to-be-tested font and the stroke data of the standard font; determining the to-be-tested stroke that is matched with each standard stroke of the standard font one by one among each to-be-tested stroke of the to-be-tested font according to the difference, and forming an index pair by combining the first stroke order index of each standard stroke with the second stroke order index of the to-be-tested stroke matched with each standard stroke; and generating a writing evaluation result of the to-be-tested font in the stroke order evaluation dimension according to the index pair. The application can effectively evaluate the case that the writing is correct but the stroke order is wrong in the writing process of children.

The invention discloses a Chinese character digitalization coding model based on positive and negative heterozygotes. The model maps 98 basic components into unique rational data positive and negative one-bit numerical codes respectively; converting the Chinese character into an ordered positive and negative digital sequence according to the hierarchy, radical and stroke order rule; the sequence is directly converted into a unique binary machine code through a Chinese information exchange standard code table; according to the method, the storage space of the Chinese character information is greatly compressed, massive Chinese characters are disassembled into only 98 basic components to be coded and stored, the mode that tens of thousands and even hundreds of thousands of Chinese character font data need to be independently stored in a traditional scheme is replaced, the storage requirement of a Chinese character library is lowered from the megabyte level to the kilobyte level, and the storage efficiency of the Chinese character library is improved. And hardware storage resources are greatly saved.

The embodiment of the invention provides a writing stroke order correcting method and device, equipment, a medium and a program product. The writing stroke order correcting method comprises the steps that track data of Chinese character writing of a user is obtained; a user stroke label sequence corresponding to the track data is determined through a stroke time sequence classification model, and the user stroke label sequence is used for representing the input stroke sequence of the user writing the Chinese character; based on a standard stroke order rule, matching the user stroke label sequence with a standard stroke label sequence, and determining a stroke order correction result; and generating a stroke order correction report according to the stroke order correction result. A writing process is precisely restored through track data, dynamic writing is converted into a structured tag sequence by utilizing a stroke time sequence classification model, and then multi-dimensional matching is performed on the structured tag sequence and a standard stroke order rule, so that fine-grained and high-accuracy stroke order correction is realized, and interpretable feedback is provided for a user.