Document Analysis with the OCRopus OCR Platform

• Overview of OCRopus a general overview of the OCRopus architecture
• goals, information flow, general architecture
  

• Introduction to OCRopus basic information about OCRoups
  
• installing, running, and extending OCRopus; Lua scripting; writing C++ extensions

Developing With and For OCRopus

• Scripting OCRopus in Lua
  
• introduction to Lua scripting and Lua modules available from within OCRopus
  
• Extending OCRopus in C++
  
• writing code using OCRopus as a library, and writing new OCRopus components; building, linking; basic data structures; overview of core data structures
• Debugging Graphics (dgraphics)
• simple image display functions
  
• The C/Lua Embedding
• how to embed OCRopus in C programs, bind it to other scripting languages, etc.

Image Processing

• Image Processing general purpose linear and non-linear image processing functions
• Gaussian filters, FIR/IIR/FFT filters, feature detection, median and rank filters, edge detection,corner detection
  
• Binary and Morphological Image Processing efficient document image processing and cleanup using fast morphology
• morphological decomposition, bit-blit and run-length based implementations, output complexity, marker morphology, applications to document cleanup and layout analysis

The OCR Interfaces

• OCR Interfaces interface classes to OCR components
• pluggable algorithms and extensibility
  
• Binarization automatic and adaptive document image binarization and segmentation
• review of standard document binarization methods, fast integral-image based implementations of adaptive binarization methods
• Skew Detection skew detection and correction, dewarping
  
• overview of skew detection methods based on the docstrum, Fourier transforms, mathematical morphology, line fitting and RANSAC; detailed description of robust least square matching for skew correction
  
• Text-Image Segmentation text/image segmentation in documents
• local image features used for pixel and region classification, logistic regression and decision tree based classification
  
• Layout Analysis geometric document layout analysis
• review of morphological layout analysis, docstrum, XY cut, Voronoi methods, whitespace methods, and computational geometry methods
• Isolated Character Recognition the isolated character recognition interfaces
• usage and function of the interface
  
• Text Line Recognition the text line recognition interfaces
• usage and function of the interface
• WFST Operations and Basic Language Modeling
• weighted finite state transducers, composition, search, relationship to HMMs; "classical" language models, including n-graphs, n-grams, dictionaries, and tries; expression of classical language models in weighted finite state transducers
• hOCR Output Generation
• DOM generation, DOM scripting for layout analysis; alternative output formats
  

More on Algorithms

• OCR by Oversegmentation text line recognition using oversegmentation
• recognition by oversegmentation, grouping, and segmentation graphs; different methods for oversegmentation (upper contour, skeletal graph, dynamic programming); relationship to HMMs; statistically sound estimation of segmentation costs and posterior probabilities; relationship to speech recognition and HMM-based methods
• Adaptation of Character Recognizers improving performance by taking advantage of style consistency within documents
  
• parametric adaptation, script and font recognition, shape dictionary augmentation, shape clustering, co-training, stochastic gradient descent, mixture models, hierarchical Bayesian methods
• Adaptation of Language Models improving performance by taking advantage of language model consistency within documents
• language recognition, dictionary augmentation, language model adaptation
  

More on Extending

• Integrating Your Own OCR and Layout
• interfaces and strategies for integrating your own OCR and layout analysis code into OCRopus, for evaluation, testing, and production use
• Future Work and Contributions
• some hints about current status and areas of work; relationship to published methods; parametric adaptation; requests for contributions
  

Additional Topics

• Statistical Layout Analysis statistical document layout analysis
• an overview of statistical approaches to layout analysis, including MRFs, stochastic 2D grammars, 2D HMMs, turbo decoding, and structural mixture models
• Shape Based Recognition shape clustering for OCR
• clustering methods for OCR, both for style modeling and for speeding up OCR engines; contour-based methods; shape matching-based methods; statistically sound modeling of shape variations
  
• Advanced Statistical Language Modeling statistical language modeling for OCR using WFSTs and the OpenFST library
  
• smoothing; representation of recognition alternatives; integration with statistical natural language post-processing, including information extraction; use of WFST models for training OCR with misaligned ground truth
• Camera-Based Dewarping Methods
• brief overview of image dewarping methods and camera-based methods
• More Performance Evaluation
  
• an overview of layout performance evaluation metrics; color-based pixel-accurate ground truth representation; bipartite matching and computation of vectorial performance scores; evaluation of segmentation performance; evaluation of character recognition performance
• Document Image Degradation artificially generating degraded document image
• degradation models; applications to training data generation
• Performance Evaluation benchmarking and performance evaluation
• edit distance computations; hocr tools
• Constrained Text Line Finding for Layout Analysis
  
• a general-purpose layout analysis method that you can easily customize