80 results about "Single character" patented technology

The invention relates to a method, a device and equipment for identifying ancient characters of a war bamboo slip, and a medium. The method comprises the following steps: acquiring a to-be-identified war bamboo slip image containing a plurality of ancient characters; flattening a local feature graph containing local detail information of ancient characters in a to-be-recognized war national bamboo slip image output by the OfficientNetV2 convolutional neural network into a sequence structure, and splicing the sequence structure with a feature sequence containing global semantic information and long-range dependency information of the ancient characters output by a Transform encoder in a channel dimension to form a joint feature tensor; layer normalization processing is carried out; and inputting the combined feature tensor subjected to layer normalization processing into a classification module of an ancient character recognition model so as to output a single character recognition result corresponding to a single ancient character or character sequence recognition results corresponding to a plurality of continuous ancient characters. Compared with the prior art, the method has better supplementing and repairing capacity when processing defective and broken strokes, and the recognition capacity for characters with incomplete structures or complex forms is remarkably improved.

The invention provides a composition correction method and device based on a large model, and the method comprises the steps: collecting a paper document containing a handwriting composition of a user, and generating a digital composition picture; performing stroke feature vector extraction on each single character; obtaining an identification result and confidence corresponding to each single character image; screening out single characters of which the confidence coefficient is greater than a first threshold value as quasi-recognition characters; determining the grammar accuracy of the statement where each quasi-recognition character is located; constructing a handwritten stroke library of the user according to the extracted stroke feature vectors; the stroke feature vector of each single character is corrected, and the recognition result and the confidence coefficient corresponding to each single character image are obtained again until the proportion of the number of the quasi-recognition characters is not lower than a second threshold value; determining composition content according to all single character recognition results; and based on a plurality of pre-trained composition evaluation large models, evaluating the composition content from different evaluation angles, and giving scores and comments. The composition correcting efficiency, accuracy and consistency are improved.

The invention relates to a character recognition system and method and a storage medium, and relates to the technical field of character recognition, and the system comprises an input module which is used for reading an original image; the preprocessing module is used for preprocessing the original image; the character detection module is used for extracting a character region image in the original image; the character segmentation module is used for segmenting the character region image to obtain a single character image; the character recognition module is used for extracting character features of the single-character image and inputting the character features into a character recognition model to obtain a character recognition result, and the character recognition model is used for determining a character probability value matched with the character features and determining the character recognition result; the decryption module is used for decrypting the encrypted characters; the output module is used for outputting the decrypted text; the control module is used for calling all the modules in sequence. According to the scheme, the time and the error rate of manual operation can be reduced, and the processing efficiency is remarkably improved.

The application provides a steel pipe multi-line handwritten character detection method and device, electronic equipment and storage medium, relates to the technical field of steel pipe handwritten character detection method, and comprises the following steps: extracting a multi-line handwritten character region on a steel pipe image to obtain a character region image containing multi-line handwritten characters; converting the character region image into a gray scale image; equally cutting the gray scale image along the vertical direction to obtain a plurality of vertical segment images; obtaining a corresponding projection curve for each vertical segment image by using a horizontal projection method, and determining a character line region of each line of characters according to the projection curve of the vertical segment image; extracting a single character region in the character line region; and performing character recognition on the single character region on the steel pipe image by using a preset recognition model to obtain a recognition result. The application can be applied to the recognition of handwritten characters on a steel pipe in an actual production process, and can efficiently and accurately recognize handwritten characters on the steel pipe.

The present invention provides an image processing device, an image processing system, an output device, an image processing method, and an image processing program that can improve the accuracy of character recognition for characters that are close to each other. [Solution] The acquisition processing unit 111 acquires image data containing characters. The rectangle candidate detection processing unit 113 detects character rectangle candidates from the image data and calculates the confidence level of the detected rectangle candidates. The single character extraction processing unit 114 corrects the confidence level of the rectangle candidates to be corrected among the first and second rectangle candidates, using a method for calculating the degree of overlap, which is selected according to the relationship between the type of the first character corresponding to the first rectangle candidate and the type of the second character corresponding to the second rectangle candidate, when at least a portion of the first and second rectangle candidates detected by the rectangle candidate detection processing unit 113 overlap with each other. The single character extraction processing unit 114 extracts single character rectangles based on the corrected confidence level.

Embodiments of the present application provide a speech recognition content correction method and device, electronic equipment and computer readable storage medium, first continuously obtain audio data of a unit time length, and an encoding feature sequence corresponding to the audio data; according to the encoding feature sequence, obtain a plurality of candidate recognition sequences, sequence scores of the sequences, and a plurality of time sequences corresponding to the plurality of candidate recognition sequences; in the case of receiving complete audio data, re-score the candidate recognition sequences to generate a target candidate recognition sequence; finally, according to the paragraph weight ratio of the time node where the character is updated, correct the character in the target candidate recognition sequence, and output the corrected target candidate recognition sequence as the final recognition result; by introducing paragraph weight analysis of the content relationship between a single character in the sequence and the context, and correcting individual characters one by one, the final output recognition text content is more accurate.

This invention provides a character recognition method, electronic device, and storage medium for a treatment control system display. The character recognition method includes: acquiring an image from the treatment control system display; acquiring an image to be recognized containing characters; binarizing the image to be recognized; removing edge blank areas from the binarized image; performing character segmentation on the binarized image to obtain several first character image blocks, where each first character image block is either a single-character image block or a connected character image block; confirming the category of the first character image blocks and performing the following processing: if the first character image block is a single-character image block, then by matching it with a template character image, the single character in the single-character image block is recognized; if the first character image block is a connected character image block, then the connected character image block is de-connected to recognize each character in the connected character image block. This invention enables automatic recognition of planning information in a treatment control system display.

This application provides a text-image matching method, an electronic device, and a storage medium, relating to the field of data processing technology. In this method, text is first acquired; then, the text is segmented to obtain segmentation results including single characters and phrases, where a phrase includes at least two single characters; next, the feature vectors corresponding to single characters are determined using the first embedding module of a pre-trained text encoder, and the feature vectors corresponding to phrases are determined using the second embedding module of the same text encoder; the first and second embedding modules are trained at different stages; subsequently, the feature vectors corresponding to single characters and phrases are encoded to determine the text semantic vectors corresponding to the text; finally, text-image matching is performed based on the text semantic vectors. This improves the accuracy of text-image matching and effectively enhances the user experience.

Input system (1) for inputting a code comprising a string containing at least numbers, wherein the input system (1) comprises: - a touch panel (2) configured to generate a contact detection signal (20) in response to the detection of a touch input gesture performed by a user (U) on the touch panel (2), wherein the contact detection signal (20) is an indicator of contact of one or more fingers (10) on the touch panel (2) during the touch input gesture; - a processing unit (3) configured to detect the contact detection signal (20) generated by the touch panel (2) and to select a single character depending on the contact detection signal (20) corresponding to the detected touch input gesture;wherein the input system (1) is characterized in that the processing unit (3) is configured to operate in an input mode to select numbers from a first string of characters comprising all or some of the numbers “0” to “9” by performing the following steps: - Determining that the touch input gesture is performed in the form of a main swipe movement (4) corresponding to the swipe movement of at least one finger (10) on the touch field (2) from a main starting point (41) to a main end point (42), where the main swipe movement (4) is interrupted by retracting the at least one finger (10), depending on the contact detection signal (20); - Determining a swipe movement vector (40) of the main swipe movement (4) depending on the contact detection signal (20);- Selecting a number from the first row of characters depending on the swipe movement vector (40) of the main swipe movement (4) independently of the main starting point (41) on the touch field (2).;

The invention provides an instant messaging method for automatically detecting sensitive information hiding, which comprises the following steps of: 1, aiming at a configured sensitive word set, constructing a sensitive word character sequence logic organization structure, and orderly bearing a single sensitive word in the sensitive word character sequence logic organization structure through a plurality of character mapping units on the same logic path, each character mapping unit corresponds to a single character in the sensitive word, the character mapping units pass through a preset logic association relationship, and the logic association relationship represents the sequence of the characters in the sensitive word; 2, on the basis of the constructed special character set, special characters in a to-be-filtered text generated in instant messaging are filtered out, and only non-special characters are reserved to form a to-be-matched character sequence; and step 3, matching the to-be-matched character sequence with the sensitive word character sequence logic organization structure to determine sensitive information in the to-be-filtered text. According to the scheme, the missed judgment problem of a traditional scheme is solved or relieved in a targeted manner.

The invention relates to a multi-line text searching and replacing method and system, and the method comprises the steps: carrying out the preprocessing of an original multi-line text, a multi-line searching content and a multi-line replacing content, removing the head and tail spaces of each line, and obtaining a corresponding logic text, a logic searching content and a logic replacing content, judging whether the logic search content contains a preset wildcard character or not, if the logic search content does not contain the preset wildcard character, carrying out simple character string matching on the logic text to obtain a logic index search result, converting the logic index search result into an original character index by utilizing a preset index mapping relation for positioning, and executing simple replacement operation, and if the logic search content contains the preset wildcard character, carrying out simple character string matching on the logic text to obtain a logic index search result; and if the logic text is matched with the fuzzy item list, regarding the logic search content as an integral matching block, performing sliding comparison according to rows in a row array corresponding to the logic text, if the matching succeeds, extracting the fuzzy item list and the starting and stopping row indexes of the matching block, performing positioning by utilizing an index mapping relation, and executing fuzzy replacement operation of inserting the fuzzy item list into a placeholder.

The invention provides a document analysis method and device, equipment, a storage medium and a product, and the method comprises the steps: carrying out character prediction based on a document page image and text prompt information indicating analysis, and generating a target character; performing character prediction based on the target character and a set prediction guide unit, and generating at least two characters of which the character positions are ranked behind the target character; if the ending character is not obtained, taking at least two characters as target characters, and performing character prediction again based on the target characters and the prediction guide unit until the ending character is obtained; and based on the characters obtained by each prediction, an analysis result is generated, and the analysis result comprises text information used for representing the content elements in the document page image and the structural relationship between the content elements. According to the technical scheme, the prediction guiding unit is introduced, so that multiple characters can be predicted in parallel in single character prediction, and the document analysis speed is increased while the document analysis accuracy is kept.

The invention discloses a method and device for recognizing and reconstructing vector characters of a CAD drawing, and relates to the technical field of data processing. The method comprises the steps that a PDF file is analyzed, and vector elements and attribute information of the vector elements are extracted; character stroke candidate lines are screened out according to attribute grouping; carrying out connectivity analysis and density-based spatial clustering on the lines, and identifying a text region; rendering the vector lines of the text region into an image with high resolution, carrying out single character segmentation, and recognizing characters by combining drawing-level font library template matching with a single character recognition model; combining the single characters into word groups according to the positions and the context information, and performing word order correction by adopting a language model; the recognition result is written back into an editable CAD text object; according to the method, vector geometric information is directly utilized, distortion of bitmap sampling is avoided, the small character recognition rate and the anti-jamming capability are effectively improved, and end-to-end semantic recovery from vector lines to searchable and editable texts is achieved.

The invention provides a character practice method and device, electronic equipment, a storage medium and a product. The method comprises the following steps: shooting in real time to obtain a user exercise book image; identifying grids in the exercise book image and determining a to-be-exercised area; the to-be-practiced area is matched with a standard grid in a character action model to determine the display position of the virtual action model in the to-be-practiced area, and the character action model is a dynamic three-dimensional model containing a hand action track in the process that a single character is written in the standard grid; the to-be-exercised characters are exercised based on the display position and the character action model, a learner can learn according to own time arrangement and rhythm and can also select characters needing to be exercised according to own requirements, the space-time flexibility of character exercise is improved, and personalized teaching is achieved.

The application discloses an image recognition method and device based on chroma domain positioning and topological constraint, relates to the technical field of data processing, and comprises the following steps: after an input image is preprocessed, an initial mask is generated in combination with contrast criteria and darkness criteria, pseudo targets are removed through hole-preserving connected domain analysis and Euler number filtering; rendering is performed by using an artificial color embedding technology, chroma domain positioning is performed in an HSV space, and an MRZ region is extracted; an inclination angle is estimated based on edge line direction consistency, and a maximum inscribed rectangle cutting is performed to obtain an MRZ cutting region; character segmentation is performed based on format constraint, an uncertainty conduction scheduling mechanism is adopted to adjust segmentation parameters and a retry strategy, and multiple single-character images are output; HOG features are extracted from the single-character images, a character classification is performed by using an SVM classifier, and preliminary recognition results and classification scores of each character are obtained; a final recognition score is fused based on structure prior scores and classification scores, and complete MRZ text is output.

The invention provides an automatic limit line forming circular grid writing method, relates to the technical field of Chinese character writing training of primary and secondary school students, and aims to solve the core pain points that the font size is difficult to control during writing of the primary and secondary school students and the handwriting is easy to skew when being switched to a transverse line / blank paper. The core of the method is a round grid composed of an outer circle with the diameter of 6 mm and a central inner square with the side length of 2 mm, the round grid is matched with a standard composition grid with the diameter of 8 mm, and a blank space with the diameter of 1 mm is formed; the method is realized through four-step training of practicing a single character by a single round grid, practicing coherent writing by a row of round grids, alternately transitioning round grids and transverse lines, and challenging a reference line at the top of blank paper, and is combined with a special exercise book, an indentation ruler or light-color printing. By means of the method, the paper surface neatness of composition grid writing can be immediately improved, the students can form muscle memory through training of the psychological datum line, finally, the students can also write neatly on the blank paper, and the method is suitable for the students of the third grade and above of the primary school and is a scientific and practical writing training system.

The present application relates to the image processing technical field in machine vision, especially relates to the high-voltage transmission line inspection image processing field in power system, and specifically relates to a kind of character detection and identification method in power pole information board image.The power pole information board image is preprocessed first;Then the feature points of the power pole information board image after preprocessing are obtained, and the character candidate region is obtained;Remove the non-character region in the character candidate region, obtain single character region;Single character region is merged into text line;Text line is recognized by character.This application makes full use of the advantages of MSER detection natural scene text, gives full play to the advantages of Imbinarize-MSER local feature multi-scale detection, candidate region stability is good, affine invariance, and the character detection and identification of the power pole information board collected, facilitate monitoring and management the running state of transmission line, provide security for the safety of transmission line.

A training method includes: obtaining a synthesis text image set, a synthesis text image being obtained through synthesizing a real scenario background image and a random word, the synthesis text image being provided with a line text annotation box and a single character annotation box; training an initial algorithm network using the synthesis text image set, so as to obtain an intermediate model; processing a real scenario text image set using the intermediate model, so as to obtain a pseudo label of a real scenario text image, the real scenario text image being provided with a line text annotation box, the pseudo label being a single character annotation box; and training the intermediate model using the synthesis text image set and the real scenario text image set having the pseudo label, so as to obtain the single character detection model.

The application discloses an intelligent display voice-to-text method and system and a medium, and the method comprises the following steps: when an audio and video file is captured, the audio and video file is converted into text; each sentence of text is segmented according to a pre-agreed punctuation mark to obtain segmented sentence text information; a pre-established dictionary table is searched; if historical data corresponding to the segmented sentence text information is found in the dictionary table, a corresponding previously combined text paragraph is obtained from the dictionary table; the text paragraph is rendered; single characters in the rendered text paragraph content are processed according to sensitive words, forbidden words or search words; and the processed single characters are synchronized with the text paragraph on a page for display. Through the application, a user can quickly find out where a violation is located, and can also quickly jump to a corresponding progress for manual auditing to confirm whether a problem exists, thereby greatly reducing the workload of the user for compliance processing.

The invention discloses an optical character recognition method for assisting teaching, and belongs to the technical field of image processing. The method comprises the following steps: firstly, acquiring a handwritten text image and segmenting a single character image, then acquiring direction intensities of eight direction intervals according to a character image pixel gradient direction, determining direction dominance according to a ratio of the maximum direction intensity to the total direction intensity, and obtaining a direction dominance distribution image; and meanwhile, calculating the direction sudden change intensity of each pixel point, and generating a direction sudden change intensity distribution image. Performing feature enhancement on the character image, the direction dominance distribution image and the direction abrupt change intensity distribution image, and extracting a stroke feature map and a turning feature map; and finally, performing multi-level feature extraction and fusion on the two types of feature maps, completing classification recognition by using a full connection layer, and outputting a recognition result, thereby effectively improving the precision of optical character recognition of the handwritten text.

The application discloses an OCR character recognition method, an electronic device and a storage medium, obtains text data to be recognized, carries out preprocessing on the text data to obtain a text image, extracts feature information of the text image, labels data for training to obtain a corresponding training model, carries out prediction positioning and clipping on a text region of the text image according to the training model, carries out rotation correction on the text image through a rotation correction model of the picture to obtain a target text image, carries out segmentation on characters in the target text image to obtain a character region, vertically maps points on the character region to the lowest position, takes a statistical result of each position point as a segmentation character standard, divides multiple characters in the text into single characters, feeds the segmented single characters into an OCR recognition engine for character recognition, and outputs recognized characters, so that the text image is quickly segmented and accurately recognized, and thus the OCR character recognition efficiency is improved.

The present disclosure relates to an image processing method, device, readable storage medium and electronic equipment. The method comprises: extracting a text line region from a target image; for each text line region, performing segmentation on the text line region to obtain at least one single character image corresponding to the text line region; and inputting the at least one single character image corresponding to the text line region into a pre-trained character recognition model to obtain recognized text corresponding to the text line region. Since text recognition is performed according to each single character image corresponding to the text line region, the influence of character gaps in the text line region on the text recognition result can be avoided, thereby improving the accuracy of text recognition. In addition, text recognition is simultaneously performed according to each single character image corresponding to the text line region, rather than performing recognition on each single character image respectively, thereby being able to capture the correlation features between adjacent characters in the text line region, thereby further improving the accuracy of text recognition.

The application provides a shape robustness text detection method based on improved CharNet and a system thereof. Step 1, inputting an image to be detected into a CharNet network; step 2, performing backbone network feature extraction on the image to be detected to form a feature map; step 3, inputting the feature map into two parallel branches of the CharNet network respectively, wherein the two parallel branches include a character branch for single character detection and recognition and a text instance detection branch for predicting a text instance bounding box; step 4, obtaining character recognition information based on the character branch for single character detection and recognition; step 5, obtaining character position information based on the text instance detection branch for predicting a text instance bounding box; and step 6, integrating the character recognition information and the character position information to obtain a text recognition result. The method is used to solve the problems of extremely long text and arbitrary shape text that are difficult to identify in text recognition.

The application discloses a zero watermark generation method and device, equipment, medium and product, and the method comprises the following steps: constructing a first character quantity set according to the quantity of each key character in the code data to be protected, wherein the key character is a single character defined in advance; constructing a first feature matrix according to the size relationship of different elements in the first character quantity set; and generating a zero watermark image based on a preset watermark image and the first feature matrix. The embodiment of the application realizes deep adaptation with the characteristics of the code data, does not need to embed the code to be protected, does not modify the code file, and can avoid destroying the original business logic of the code.

Embodiments of the present specification provide an image tampering detection method and device, the method comprising: when tampering detection is performed on a target image, obtaining the target image, the target image being a screenshot image, and the target image including characters; performing single character extraction on the characters in the target image to obtain at least one single character; and determining whether the target image is tampered with according to character features of the at least one single character.

Embodiments of the present application provide a handwritten signature recognition method and device, electronic equipment and storage medium. The handwritten signature recognition method comprises: obtaining a handwritten signature picture to be recognized; performing single character detection on the handwritten signature picture to obtain position information of a target character region; merging target character regions that need to be merged based on the position information to obtain a merged character region; recognizing characters corresponding to each character region, the character region including the target character region that has not been merged and the merged character region; comparing the characters with a user name in user information, and determining that a handwritten signature in the handwritten signature picture is valid when the comparison result is consistent. The handwritten signature recognition method can improve the accuracy of handwritten signature recognition.

The present application provides an energy big data cleaning method, device and equipment and storage medium, the method comprises: obtaining the text data to be cleaned, converting each character in the text data to be cleaned into a single character vector respectively, and performing word embedding processing to obtain a single character embedding vector corresponding to each character; position embedding processing is carried out on each character in the text data to be cleaned, and the position vector of each character is obtained; the position vector of each character in the text data to be cleaned is added to the corresponding single character embedding vector, the combined vector corresponding to each character is obtained, and the sequence of each character and the combined vector form a text data matrix to be cleaned; the text data to be cleaned matrix is input into the trained Transform model, and the cleaning text data output by the Transform model is obtained. The present application fuses the semantic and grammatical information of the text with the position information of the text by adopting the word embedding and position embedding operations, effectively improving the accuracy of energy big data cleaning.

The invention belongs to the technical field of character recognition, and provides an industrial character detection and recognition method and device based on a YOLO framework and a medium. The method comprises the following steps: a feature extraction module processes an industrial scene image to obtain a multi-level feature map, and a detection head predicts the spatial position of a single character based on the multi-level feature map to obtain a character rotation frame of the single character; the segmentation head carries out up-sampling on all hierarchical feature maps to the same spatial resolution and carries out splicing on a channel dimension to obtain fusion features; performing high-dimensional mapping on the fused features to obtain a high-dimensional mapping feature map; the identification head generates a sampling grid according to the affine matrix, and a sampling function aligns the high-dimensional mapping feature map to a unified output scale based on the sampling grid to obtain an aligned high-dimensional mapping feature map; and performing sequence modeling and attention decoding processing on the aligned high-dimensional mapping feature map to obtain a predicted character sequence. According to the method, a multi-branch weak supervision training mechanism is utilized, and the recognition capability of the model on unknown characters and new combinations is enhanced.

The invention provides a character recognition processing method and system for a robot, relates to the field of character recognition, and solves the technical problem that the character recognition error rate is still high due to the fact that a single character serves as a recognition object and is easily interfered by other non-characters in an image during character recognition in the prior art. The method comprises the steps of obtaining a target image of a to-be-recognized document, removing redundant images in the target image, and performing partitioning to obtain an ROI region map; inputting the ROI area graph into a character recognition model to obtain recognition characters; performing logic verification on the recognition characters based on the hierarchical lexicon to obtain a recognition text; the graded lexicon is a preset content lexicon. According to the method, the target image is segmented into the ROI area map, so that character recognition of redundant images can be reduced, character recognition is carried out through the character recognition model, and the relation between the character recognition model and the character recognition model can be captured, so that the situation of wrong character recognition is further reduced.

This invention belongs to the field of graphic data processing technology, and particularly relates to a method and system for quality inspection of engraved characters on mold surfaces. The method includes identifying single characters on an image to be inspected, constructing a sequence of characters to be inspected, comparing the content of the character sequence to be inspected with a standard character sequence to obtain a comparison result containing information on multiple engravings, missing engravings, and incorrect engravings; extracting the outline of each single character on the image to be inspected, registering the corresponding standard character outline to the outline to be inspected, constructing a tolerance band, calculating the difference between all outlines to be inspected and their corresponding tolerance bands, and summarizing the results to obtain the character defect detection result; and using the character sequence content comparison result and the character defect detection result together as the overall quality inspection result for engraved characters on the mold surface. This invention can simultaneously determine whether there are multiple engravings, missing engravings, incorrect engravings, and whether the character outline structure meets quality requirements; it can be flexibly adjusted according to different tolerance requirements and can locate the defect position on a single character.