43 results about "Single character" patented technology

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 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 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 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 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 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.

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.

The invention provides a data compression method and apparatus, an electronic device, a medium and a product. The method comprises the steps of obtaining to-be-compressed text data; determining a single character and a target text character string contained in the text data; wherein the target text character string is a text character string meeting a preset compression condition; obtaining a preset compression coding table; wherein the compressed encoding table comprises a plurality of encoding characters; determining redundant coding characters except the single character in the compressed coding table; updating the compressed encoding table to establish a first mapping relation between the single character and the corresponding encoding character in the compressed encoding table, and establishing a second mapping relation between the target text character string and the redundant encoding character in the compressed encoding table; and based on the updated compression coding table, compressing the text data to obtain a compressed data field. According to the invention, the data storage length can be reduced, so that the storage space is saved.

The invention relates to an open set character recognition method and device, electronic equipment and a storage medium. The method comprises the steps of performing character stroke analysis on a text image through a character writing sequence model to obtain a stroke image sequence corresponding to the text image; according to a stroke image sequence corresponding to the text image, performing stroke correlation analysis on each single character image set in the stroke image sequence through a writing sequence adjustment model, and adjusting the stroke image sequence to obtain an adjusted stroke image sequence; and according to the adjusted stroke image sequence, performing multi-language character recognition through a classification recognition model to obtain a character recognition result of the text image. According to the method provided by the embodiment of the invention, classification and recognition can be carried out by taking the writing stroke sequence as representation, and the recognition precision in a multi-language complex scene is improved, so that the character recognition accuracy in an open set scene is improved.

This invention discloses a method for extracting character coordinates. The method includes: inputting a target text image into a feature extraction backbone network; obtaining character segmentation features and text line segmentation features through feature fusion of different layers in the backbone network; inputting the character segmentation features and text line segmentation features into a text line segmentation module and a character segmentation module, respectively, to obtain a character segmentation heatmap and a text segmentation heatmap of the target image; and calculating the coordinates of a single character based on the character segmentation heatmap and the text segmentation heatmap. Through this method, this invention avoids redundant feature extraction; exhibits high robustness for character segmentation; accelerates network convergence and improves network segmentation efficiency; and improves the accuracy of single-character coordinate extraction by back-deriving coordinates based on CTC recognition results and combining it with character segmentation methods.

The present application relates to the technical field of speech analysis or speech recognition, and particularly relates to a method for recognizing rare character translation based on FunASR, comprising: obtaining audio data to be recognized input by a user; splitting the audio data to be recognized into frequency bands according to frequency fluctuation characteristics; analyzing frequency changes generated when pronunciation changes between single characters in the effective speech frequency band, and splitting the effective speech frequency band into frame intervals corresponding to words according to the frequency change analysis result, to obtain a plurality of word test intervals; extracting pinyin syllables of frames in each word test interval through a FunASR tool, determining rare character environment sensitivity according to the pinyin syllables, and determining an effective syllable section according to the rare character environment sensitivity; calculating syllable reliability of the effective syllable section, recognizing syllables of the effective syllable section according to the syllable reliability, and matching rare character words corresponding to the syllable recognition result in a preset dictionary library, to improve the accuracy of speech recognition.

The application discloses a word segmentation processing method and device, a server and a storage medium. The word segmentation processing method comprises the following steps: performing word segmentation processing on an original text to be segmented to obtain a first word segmentation result, wherein the first word segmentation result comprises M words; performing cutting processing on the M words according to a first cutting rule to obtain a first cutting result, wherein the first cutting rule comprises the following steps: cutting adjacent same type characters in the i-th word into a single string, and performing single character cutting on the segmented Chinese character string; performing cutting processing on the M words according to a second cutting rule to obtain a second cutting result, wherein the second cutting rule comprises the following steps: cutting adjacent same type characters in the i-th word into a single string, and not performing single character cutting on the segmented Chinese character string; performing sliding window processing on the i-th word to obtain a first word segmentation set of the i-th word; and updating the first word segmentation result by using the first word segmentation set of the i-th word. The method disclosed by the application can reduce the word segmentation cost.

The application discloses an optical character recognition method for assisting teaching and belongs to the technical field of image processing. The application first collects a handwritten text image and divides a single character image, then obtains direction intensity of 8 direction intervals according to a gradient direction of a pixel point of the character image, determines a direction dominant degree by using a ratio of maximum direction intensity and total direction intensity, and obtains a direction dominant degree distribution image; meanwhile, direction mutation intensity of each pixel point is calculated to generate a direction mutation intensity distribution image. Subsequently, feature enhancement is performed on the character image, the direction dominant degree distribution image and the direction mutation intensity distribution image, and stroke feature maps and turning feature maps are extracted. Finally, multi-level feature extraction and fusion are performed on the two types of feature maps, full connection layers are used for completing classification and recognition, and an identification result is output, so that the precision of handwritten text optical character recognition is effectively improved.

The invention provides a program conversion method and device based on a difference table and terminal device.According to the program conversion method and device based on the difference table, a project file set and a difference table set are obtained, and then a first source code file and a second source code file in the project file set are divided according to file types; and after analyzing the first source code file into an abstract syntax tree, directly converting the first source code file based on a preset conversion rule in the difference table, and after analyzing the second source code file into the abstract syntax tree, directly converting the second source code file based on the preset conversion rule in the difference table, and finally integrating to obtain a target lightweight program. According to the method, the conversion rule is packaged through the difference table and the source code file is converted, so that the condition of code errors after conversion caused by simple character string replacement in the prior art is effectively avoided, in addition, manual intervention is greatly reduced through the automatic conversion mode based on the difference table, the conversion efficiency is improved, and the conversion cost is reduced. And the dependence on experience of developers is avoided, and the conversion efficiency and accuracy of the lightweight program are remarkably improved.

Embodiments of the present disclosure provide a keyword extraction method, comprising: first acquiring a text complex network corresponding to a to-be-processed text, the text complex network comprising nodes corresponding to a plurality of single characters in the to-be-processed text, weight values of connecting edges between the plurality of nodes, strengths of the plurality of nodes and in-out degrees of the plurality of nodes; then calculating a clustering coefficient of connections between the plurality of nodes based on the strengths of the plurality of nodes, the in-out degrees of the plurality of nodes and the weight values of the connecting edges in the text complex network; thereafter calculating a proportional mixing amount of the connections between the plurality of nodes based on the in-out degrees of the plurality of nodes, the in-out degrees of nodes connected by the plurality of nodes and the number of connecting edges in the text complex network; and calculating path lengths of the connections between the plurality of nodes based on the connecting edges between the plurality of nodes; and finally extracting keywords corresponding to the to-be-processed text based on the clustering coefficient of the connections between the plurality of nodes, the proportional mixing amount and the path lengths, thereby improving the accuracy and comprehensiveness of keyword extraction.

This invention discloses a method and apparatus for real-time writing direction determination based on single-character stroke features. The method includes: acquiring a sequence of coordinate points of a stylus on a whiteboard in real time; calculating a feature set representing the writing features of a single character based on the coordinate point sequence; calculating a horizontal comprehensive score by weighting the feature set; calculating a vertical comprehensive score by weighting the reciprocals of each feature in the feature set; and determining the writing direction of the stylus based on the horizontal and vertical comprehensive scores to obtain a determination result. This invention proposes a method and apparatus for real-time writing direction determination based on single-character stroke features. It calculates a feature set and calculates a weighted score based on the single-character stroke features in real time to determine the writing direction, without relying on multi-character layouts, thus avoiding response delays at the source and enabling independent and effective recognition of single characters. Therefore, it can solve the problems of response delays and single-character recognition failures caused by existing technologies that rely on multi-character layouts to determine writing direction.

Embodiments of the present application disclose a kind of unsupervised training method of character recognition model and related equipment.The method comprises: obtaining original image, and the original image is the image containing character;Mask processing is carried out to part of pixel of original image, and mask image is obtained, and the mask image contains pixel masked area and pixel unmasked area;Mask image is input into neural network model, and the information of character of pixel masked area is predicted based on the information of character that pixel unmasked area has using neural network model, and prediction result is obtained, wherein, the information of character is the information of partial structure with single character and / or the information of several complete characters, or the information without character;Based on prediction result and the original image, the parameters of neural network model are updated.The present application solves the technical problem that existing unsupervised character recognition cannot finely learn the structure information of single character.

1. Name of the product in this design: Iron template (circular single character). 2. Purpose of this design: Iron formwork for building houses. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D rendering 1.

The application relates to a character information correction method and device, a storage medium and electronic equipment. The method comprises the following steps: obtaining text content and spatial coordinate information of each text region in a target micro-drama picture, clustering all the text regions based on spatial distance relationships, and obtaining a first character identification result; inputting the target micro-drama picture into a visual large model to perform visual reasoning on the target micro-drama picture, and obtaining a second character identification result; comparing the first character identification result with the second character identification result, and performing verification processing on the second character identification result according to a comparison result, and obtaining a verified character identification result; in the case that the number of second character names is greater than the number of first character names, performing merging and deduplication processing on the verified character identification result according to the first character identification result, and obtaining a final character identification result. The application solves the technical problem that a large model is prone to misdivide single character information, thereby causing character identification errors.

A method includes comparing a first field of a first data record to a first field of a second data record to determine a first similarity metric based on a number of single character changes used to convert a value of the first field of the first data record to a value of the first field of the second data record and comparing a second field of the first data record to a second field of the second data record to determine a second similarity metric based on whether the second field of the first data record is identical to a value of the second field of the second data record. The method includes determining an aggregate similarity metric based on at least the first similarity metric and the second similarity metric and assigning the second data record to a calibration reliability group based on the aggregate similarity metric.