Phong et al., 2022 - Google Patents
An end‐to‐end framework for the detection of mathematical expressions in scientific document imagesPhong et al., 2022
View PDF- Document ID
- 11745159456809428434
- Author
- Phong B
- Hoang T
- Le T
- Publication year
- Publication venue
- Expert Systems
External Links
Snippet
The detection of mathematical expressions is a prerequisite step for the digitisation of scientific documents. Many different multistage approaches have been proposed for the detection of expressions in document images, that is, page segmentation and expression …
- 238000001514 detection method 0 title abstract description 193
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/21—Text processing
- G06F17/22—Manipulating or registering by use of codes, e.g. in sequence of text characters
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
- G06K9/34—Segmentation of touching or overlapping patterns in the image field
- G06K9/342—Cutting or merging image elements, e.g. region growing, watershed, clustering-based techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00442—Document analysis and understanding; Document recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Grüning et al. | A two-stage method for text line detection in historical documents | |
Poco et al. | Reverse‐engineering visualizations: Recovering visual encodings from chart images | |
Vo et al. | Text line segmentation using a fully convolutional network in handwritten document images | |
Mouchère et al. | Advancing the state of the art for handwritten math recognition: the CROHME competitions, 2011–2014 | |
US11651150B2 (en) | Deep learning based table detection and associated data extraction from scanned image documents | |
CN112949476B (en) | Text relation detection method, device and storage medium based on graph convolution neural network | |
Phong et al. | An end‐to‐end framework for the detection of mathematical expressions in scientific document images | |
Huang et al. | Isolated Handwritten Pashto Character Recognition Using a K‐NN Classification Tool based on Zoning and HOG Feature Extraction Techniques | |
Kalyoncu et al. | GTCLC: leaf classification method using multiple descriptors | |
Jindal et al. | Text line segmentation in indian ancient handwritten documents using faster R-CNN | |
US20150213313A1 (en) | Methods and systems for efficient automated symbol recognition using multiple clusters of symbol patterns | |
US20150213330A1 (en) | Methods and systems for efficient automated symbol recognition | |
Traquair et al. | Deep learning for the detection of tabular information from electronic component datasheets | |
Capobianco et al. | Historical handwritten document segmentation by using a weighted loss | |
Nguyen | TableSegNet: a fully convolutional network for table detection and segmentation in document images | |
Stewart et al. | Document image page segmentation and character recognition as semantic segmentation | |
Li et al. | Multilingual text detection with nonlinear neural network | |
Naseer et al. | Meta‐feature based few‐shot Siamese learning for Urdu optical character recognition | |
Lee et al. | Deep learning-based digitalization of a part catalog book to generate part specification by a neutral reference data dictionary | |
Gal et al. | Cardinal graph convolution framework for document information extraction | |
Liu et al. | A novel SVM network using HOG feature for prohibition traffic sign recognition | |
Nguyen et al. | CDeRSNet: Towards high performance object detection in Vietnamese document images | |
Fornés et al. | The ICDAR/GREC 2013 music scores competition: Staff removal | |
Mahajan et al. | DELIGHT-Net: DEep and LIGHTweight network to segment Indian text at word level from wild scenic images | |
Brodić et al. | Identification of fraktur and latin scripts in german historical documents using image texture analysis |