"Example centric document design and development"
Wilcoxon-Mann-Whitney statistic
http://en.wikipedia.org/wiki/Mann%E2%80%93Whitney_U
Spearman Correlation Coefficient
http://en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient
Blueprint - Adobe Labs
Perceptron
http://en.wikipedia.org/wiki/Perceptron
"Feature relevance analysis for writer identification"
Freeman chain codes
http://en.wikipedia.org/wiki/Chain_code
Grapheme
http://en.wikipedia.org/wiki/Grapheme
Chi-squared
http://en.wikipedia.org/wiki/Chi-square_test
"Using perturbed handwriting to support writer identification in the presence of data constraints"
MGH - Model Generated Handwriting
MPG - Model Perturbed Handwriting
"Text-Independent Writer Identification and Verification on Offline Arabic Handwriting"
Bulacu, Schomaker, Brink 2007
SVM (Support Vector Machine) with radius basis kernel
McNemar's Test
http://en.wikipedia.org/wiki/McNemar%27s_test
"Statistical characterization of handwriting characteristics using automated tools"
Probabalistic Graphical Model
http://en.wikipedia.org/wiki/Graphical_model
Sunday, January 30, 2011
Document Recognition and Retrieval. Electronic Imaging Conference. 26-Jan-2011
Capture: Image to Archive (conference)
Scene Analysis "Functional Role Labeling"
Image Template -> template management
Trainable pattern classifiers. Features + Classifiers.
Features
--------
Haar
runlength
Fourier
word counts
Classifiers
-----------
Decision tree
nearest neighbor
SVM (Support Vector Machine)
generative probability
density
"Learning Image Anchor Templates for Document Classification and Data Extraction"
Sarkar. http://www.icpr2010.org/pdfs/icpr2010_ThAT7.5.pdf
Constellation Model
http://en.wikipedia.org/wiki/Constellation_model
Information extraction by finding repeated structure
Evgeniy Bart, Prateek Sarkar
http://dx.doi.org/10.1145/1815330.1815353
Best First Leaf Search (from aforementioned paper)
NIST tax form data sets
http://www.nist.gov/srd/nistsd2.cfm
"Introduction of Statistical Information in a Syntactic Analyzer for Document Image Recognition"
Sayre's Paradox
http://dx.doi.org/10.1016/0031-3203(73)90044-7
Hidden Markov Model
http://en.wikipedia.org/wiki/Hidden_Markov_model
"MRF Model w/ Parameter Optimization by CRF for online recognition of handwritten Japanese characters"
MRF - Markov Random Field
http://en.wikipedia.org/wiki/Markov_random_field
CRF - Conditional Random Field
http://en.wikipedia.org/wiki/Conditional_random_field
Extract feature points using Ramner method
U. Ramer “An Iterative Procedure for the Polygonal Approximation of Plan Closed Curves” Computer Graphics and Image Processing, vol.1, pp244-256, 1972.
http://dx.doi.org/10.1016/S0146-664X(72)80017-0
Stochastic Gradient Descent
http://en.wikipedia.org/wiki/Stochastic_gradient_descent
Viterbi algorithm
http://en.wikipedia.org/wiki/Viterbi_algorithm
Baum-Welch algorithm
http://en.wikipedia.org/wiki/Baum%E2%80%93Welch_algorithm
Elastic matching
http://en.wikipedia.org/wiki/Elastic_Matching
"Improving an HMM based offline handwriting recognition system using MME-PSO optimization"
MME -
PSO - Particle Swarm Optimization
http://en.wikipedia.org/wiki/Particle_swarm_optimization
MD-LSTM
http://en.wikipedia.org/wiki/Long_short_term_memory
HTK - toolkit for building HMMs (Cambridge)
http://htk.eng.cam.ac.uk/
"Segmenting text from outdoor images taken by mobile phones using color features"
Preprocessing:
RGB -> HSI
histogram equalization Intensity channel
HSI -> RGB
Image binarization
Noise removal
Image Segmentation.
http://people.cs.uchicago.edu/~pff/
"Font and Background Color Independent Text Binarization"
Kasar edge cue based algorithm
http://www.imlab.jp/cbdar2007/proceedings/papers/O1-1.pdf
Levenshtein Distance
http://en.wikipedia.org/wiki/Levenshtein_distance
Bag of Words
http://en.wikipedia.org/wiki/Bag_of_words_model_in_computer_vision
Local Adaptive Binarization
"Perceptive Method for Handwritten Text Segmentation"
Kalman Filtering
http://en.wikipedia.org/wiki/Kalman_filter
Delaunay graph for distance computation
http://en.wikipedia.org/wiki/Delaunay_triangulation
DMOSp
"A masked based enhancement method for historical documents"
Filtering (noise reduction)
- Wiener
http://en.wikipedia.org/wiki/Wiener_filter
- Median
http://en.wikipedia.org/wiki/Median_filter
Markov Random Fields
http://en.wikipedia.org/wiki/Markov_random_field
Local Binarization [Gatos 2006]
"Adaptive degraded document image binarization"
http://dx.doi.org/10.1016/j.patcog.2005.09.010
OCR - Tesseract
http://en.wikipedia.org/wiki/Tesseract_%28software%29
Scene Analysis "Functional Role Labeling"
Image Template -> template management
Trainable pattern classifiers. Features + Classifiers.
Features
--------
Haar
runlength
Fourier
word counts
Classifiers
-----------
Decision tree
nearest neighbor
SVM (Support Vector Machine)
generative probability
density
"Learning Image Anchor Templates for Document Classification and Data Extraction"
Sarkar. http://www.icpr2010.org/pdfs/icpr2010_ThAT7.5.pdf
Constellation Model
http://en.wikipedia.org/wiki/Constellation_model
Information extraction by finding repeated structure
Evgeniy Bart, Prateek Sarkar
http://dx.doi.org/10.1145/1815330.1815353
Best First Leaf Search (from aforementioned paper)
NIST tax form data sets
http://www.nist.gov/srd/nistsd2.cfm
"Introduction of Statistical Information in a Syntactic Analyzer for Document Image Recognition"
Sayre's Paradox
http://dx.doi.org/10.1016/0031-3203(73)90044-7
Hidden Markov Model
http://en.wikipedia.org/wiki/Hidden_Markov_model
"MRF Model w/ Parameter Optimization by CRF for online recognition of handwritten Japanese characters"
MRF - Markov Random Field
http://en.wikipedia.org/wiki/Markov_random_field
CRF - Conditional Random Field
http://en.wikipedia.org/wiki/Conditional_random_field
Extract feature points using Ramner method
U. Ramer “An Iterative Procedure for the Polygonal Approximation of Plan Closed Curves” Computer Graphics and Image Processing, vol.1, pp244-256, 1972.
http://dx.doi.org/10.1016/S0146-664X(72)80017-0
Stochastic Gradient Descent
http://en.wikipedia.org/wiki/Stochastic_gradient_descent
Viterbi algorithm
http://en.wikipedia.org/wiki/Viterbi_algorithm
Baum-Welch algorithm
http://en.wikipedia.org/wiki/Baum%E2%80%93Welch_algorithm
Elastic matching
http://en.wikipedia.org/wiki/Elastic_Matching
"Improving an HMM based offline handwriting recognition system using MME-PSO optimization"
MME -
PSO - Particle Swarm Optimization
http://en.wikipedia.org/wiki/Particle_swarm_optimization
MD-LSTM
http://en.wikipedia.org/wiki/Long_short_term_memory
HTK - toolkit for building HMMs (Cambridge)
http://htk.eng.cam.ac.uk/
"Segmenting text from outdoor images taken by mobile phones using color features"
Preprocessing:
RGB -> HSI
histogram equalization Intensity channel
HSI -> RGB
Image binarization
Noise removal
Image Segmentation.
http://people.cs.uchicago.edu/~pff/
"Font and Background Color Independent Text Binarization"
Kasar edge cue based algorithm
http://www.imlab.jp/cbdar2007/proceedings/papers/O1-1.pdf
Levenshtein Distance
http://en.wikipedia.org/wiki/Levenshtein_distance
Bag of Words
http://en.wikipedia.org/wiki/Bag_of_words_model_in_computer_vision
Local Adaptive Binarization
"Perceptive Method for Handwritten Text Segmentation"
Kalman Filtering
http://en.wikipedia.org/wiki/Kalman_filter
Delaunay graph for distance computation
http://en.wikipedia.org/wiki/Delaunay_triangulation
DMOSp
"A masked based enhancement method for historical documents"
Filtering (noise reduction)
- Wiener
http://en.wikipedia.org/wiki/Wiener_filter
- Median
http://en.wikipedia.org/wiki/Median_filter
Markov Random Fields
http://en.wikipedia.org/wiki/Markov_random_field
Local Binarization [Gatos 2006]
"Adaptive degraded document image binarization"
http://dx.doi.org/10.1016/j.patcog.2005.09.010
OCR - Tesseract
http://en.wikipedia.org/wiki/Tesseract_%28software%29
Electronic Imaging Conference. 26-Jan-2011
Keynote: "Problems in Biological Imaging: Opportunities for Signal Processing"
PSF - Point Spread Function
http://en.wikipedia.org/wiki/Point_spread_function
Restoration: Denoise, Deconvolution.
http://en.wikipedia.org/wiki/Deconvolution
Hysteresis
http://en.wikipedia.org/wiki/Hysteresis
Segmentation
- thresholding
http://en.wikipedia.org/wiki/Thresholding_%28image_processing%29
- watershed
http://en.wikipedia.org/wiki/Watershed_%28image_processing%29
PSF - Point Spread Function
http://en.wikipedia.org/wiki/Point_spread_function
Restoration: Denoise, Deconvolution.
http://en.wikipedia.org/wiki/Deconvolution
Hysteresis
http://en.wikipedia.org/wiki/Hysteresis
Segmentation
- thresholding
http://en.wikipedia.org/wiki/Thresholding_%28image_processing%29
- watershed
http://en.wikipedia.org/wiki/Watershed_%28image_processing%29
Electronic Imaging Conference. 25-Jan-2011
Keynote. "New Dimensions in Image Quality"
Full Reference (have pristine original)
"Blind" - no reference
MSE - Mean Squared Error
Spearman Correlation
http://en.wikipedia.org/wiki/Spearman_correlation
Hysterisis
http://en.wikipedia.org/wiki/Hysteresis
LIVE VQA
http://live.ece.utexas.edu/research/quality/live_video.html
- Natural Images obey statistical laws
- Our brain adapted to these statistics over eons
Natural Scene Statistics
- gaussian scale mixture (GSM)
http://en.wikipedia.org/wiki/Location_testing_for_Gaussian_scale_mixture_distributions
- generalized gaussian distribution (GGD)
http://en.wikipedia.org/wiki/Generalized_normal_distribution
Augmented Reality.
ISO 3664. Viewing Conditions.
http://www.iso.org/iso/catalogue_detail?csnumber=43234
ISO 13655. Metrology.
http://www.iso.org/iso/catalogue_detail.htm?csnumber=22476
USB2000 UV-VIS Spectronomer
http://www.oceanoptics.com/Products/usb2000+.asp
www.create.uwe.ac.uk
Color Research European Advanced Technology Employment (CREATE)
"Human Vision Based Color Edge Detection"
Delta-E-CAM-VCS > Delta-E-00 > Delta-E-CMC
"Object Classification by Color Normalization or Calibration?"
Gray World. Buchsbaum 1980. (Color constancy algorithm)
Finlayson 1998. http://www.springerlink.com/content/nhcjvku49b4jnn5r/
Retinex
http://en.wikipedia.org/wiki/Color_constancy
Colorimetric Calibration, [lee88]
maybe http://onlinelibrary.wiley.com/doi/10.1002/col.5080130311/abstract
KOPID data set uni-koblenz.de/kopid
Histogram comparison:
- sum of squares difference (SSD)
- histogram intersection
- simplified chi-squared
Earth-Mover's Distance
http://en.wikipedia.org/wiki/Earth_mover%27s_distance
"Evaluating the Smoothness of Color Transforms"
Thor Olson: Smooth Ramps: Walking the Straight and Narrow Path through Color Space. Color Imaging Conference 1999: 57-64
journalofvision.org
Full Reference (have pristine original)
"Blind" - no reference
MSE - Mean Squared Error
Spearman Correlation
http://en.wikipedia.org/wiki/Spearman_correlation
Hysterisis
http://en.wikipedia.org/wiki/Hysteresis
LIVE VQA
http://live.ece.utexas.edu/research/quality/live_video.html
- Natural Images obey statistical laws
- Our brain adapted to these statistics over eons
Natural Scene Statistics
- gaussian scale mixture (GSM)
http://en.wikipedia.org/wiki/Location_testing_for_Gaussian_scale_mixture_distributions
- generalized gaussian distribution (GGD)
http://en.wikipedia.org/wiki/Generalized_normal_distribution
Augmented Reality.
ISO 3664. Viewing Conditions.
http://www.iso.org/iso/catalogue_detail?csnumber=43234
ISO 13655. Metrology.
http://www.iso.org/iso/catalogue_detail.htm?csnumber=22476
USB2000 UV-VIS Spectronomer
http://www.oceanoptics.com/Products/usb2000+.asp
www.create.uwe.ac.uk
Color Research European Advanced Technology Employment (CREATE)
"Human Vision Based Color Edge Detection"
Delta-E-CAM-VCS > Delta-E-00 > Delta-E-CMC
"Object Classification by Color Normalization or Calibration?"
Gray World. Buchsbaum 1980. (Color constancy algorithm)
Finlayson 1998. http://www.springerlink.com/content/nhcjvku49b4jnn5r/
Retinex
http://en.wikipedia.org/wiki/Color_constancy
Colorimetric Calibration, [lee88]
maybe http://onlinelibrary.wiley.com/doi/10.1002/col.5080130311/abstract
KOPID data set uni-koblenz.de/kopid
Histogram comparison:
- sum of squares difference (SSD)
- histogram intersection
- simplified chi-squared
Earth-Mover's Distance
http://en.wikipedia.org/wiki/Earth_mover%27s_distance
"Evaluating the Smoothness of Color Transforms"
Thor Olson: Smooth Ramps: Walking the Straight and Narrow Path through Color Space. Color Imaging Conference 1999: 57-64
journalofvision.org
Electronic Imaging Conference Notes, 24-Jan-2011
24-Jan-2011
Eigenspace
http://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors
Gabor filter bank
a linear filter used for edge detection
http://en.wikipedia.org/wiki/Gabor_filter
mean-shift clustering technique
a non-parametric feature-space analysis technique[1]. Application domains include clustering in computer vision and image processing[2].
http://en.wikipedia.org/wiki/Mean-shift
Anisotropic Diffusion
“a technique aiming at reducing image noise without removing significant parts of the image content, typically edges, lines or other details”
http://en.wikipedia.org/wiki/Anisotropic_diffusion
Bilateral filters
“A bilateral filter is an edge-preserving and noise reducing smoothing filter”
http://en.wikipedia.org/wiki/Bilateral_filter
Moving Least Squares.
“Moving least squares is a method of reconstructing continuous functions from a set of unorganized point samples”
http://en.wikipedia.org/wiki/Moving_least_squares
Non-local means.
[Buades et al. ‘05]
LARK - Locally Adaptive Regression Kernel
Denoise algorithms: LARK, BM3D, KVSD
Markov Chains
http://en.wikipedia.org/wiki/Markov_chain
Wiener Filter
“reduce the amount of noise present in a signal by comparison with an estimation of the desired noiseless signal.”
http://en.wikipedia.org/wiki/Wiener_filter
Twicing (Tukey, 1977)
MMSE - Minimum Mean Squared Error
http://en.wikipedia.org/wiki/Minimum_mean_square_error
Conference 7867. "Image Quality and System Performance"
Quality Attribute Tree
Registration - translation, rotation, scaling
"Survey of full-reference image quality metrics"
by: M. Pedersen, J. Y. Hardeberg
Eigenspace
http://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors
Gabor filter bank
a linear filter used for edge detection
http://en.wikipedia.org/wiki/Gabor_filter
mean-shift clustering technique
a non-parametric feature-space analysis technique[1]. Application domains include clustering in computer vision and image processing[2].
http://en.wikipedia.org/wiki/Mean-shift
Anisotropic Diffusion
“a technique aiming at reducing image noise without removing significant parts of the image content, typically edges, lines or other details”
http://en.wikipedia.org/wiki/Anisotropic_diffusion
Bilateral filters
“A bilateral filter is an edge-preserving and noise reducing smoothing filter”
http://en.wikipedia.org/wiki/Bilateral_filter
Moving Least Squares.
“Moving least squares is a method of reconstructing continuous functions from a set of unorganized point samples”
http://en.wikipedia.org/wiki/Moving_least_squares
Non-local means.
[Buades et al. ‘05]
LARK - Locally Adaptive Regression Kernel
Denoise algorithms: LARK, BM3D, KVSD
Markov Chains
http://en.wikipedia.org/wiki/Markov_chain
Wiener Filter
“reduce the amount of noise present in a signal by comparison with an estimation of the desired noiseless signal.”
http://en.wikipedia.org/wiki/Wiener_filter
Twicing (Tukey, 1977)
MMSE - Minimum Mean Squared Error
http://en.wikipedia.org/wiki/Minimum_mean_square_error
Conference 7867. "Image Quality and System Performance"
Quality Attribute Tree
Registration - translation, rotation, scaling
"Survey of full-reference image quality metrics"
by: M. Pedersen, J. Y. Hardeberg
SC 871. Noise, Image Processing, and their Influence on Resolution.
SC 871. Noise, Image Processing, and their Influence on Resolution.
23-Jan-2011.
Electronic Imaging Conference. 23-27 Jan, 2011
Spectrogram.
http://en.wikipedia.org/wiki/Spectrogram
Measuring noise: ISO 15739
http://www.iso.org/iso/catalogue_detail.htm?csnumber=28835
Viewing Conditions. ISO 3664.
http://www.iso.org/iso/catalogue_detail.htm?csnumber=43234
European Machine Vision Association.
http://emva.org/cms/index.php
MTF - Modulation Transfer Function
http://en.wikipedia.org/wiki/Optical_transfer_function
SFR - Spatial Frequency Response
kurtosis
http://en.wikipedia.org/wiki/Kurtosis
Image Sensors and Signal Processing for Digital Still Cameras.
http://amzn.com/0849335450
23-Jan-2011.
Electronic Imaging Conference. 23-27 Jan, 2011
Spectrogram.
http://en.wikipedia.org/wiki/Spectrogram
Measuring noise: ISO 15739
http://www.iso.org/iso/catalogue_detail.htm?csnumber=28835
Viewing Conditions. ISO 3664.
http://www.iso.org/iso/catalogue_detail.htm?csnumber=43234
European Machine Vision Association.
http://emva.org/cms/index.php
MTF - Modulation Transfer Function
http://en.wikipedia.org/wiki/Optical_transfer_function
SFR - Spatial Frequency Response
kurtosis
http://en.wikipedia.org/wiki/Kurtosis
Image Sensors and Signal Processing for Digital Still Cameras.
http://amzn.com/0849335450
SC1015. Understanding and Interpreting Images.
SC1015. Understanding and Interpreting Images.
23-Jan-2011
Electronic Imaging Conference. 23-27 Jan, 2011.
Edward Adelson
http://web.mit.edu/persci/people/adelson/
“Pictures are not taken in a vacuum--an overview of exploiting context for semantic scene content understanding” Signal Processing Magazine, IEEE
March 2006, Vol23 Issue 2.
Main subject detection. Belief map.
Duda, Hurt, and Storic. Statistical Pattern Recognition
http://amzn.com/0471056693
Earth Mover Distance
http://en.wikipedia.org/wiki/Earth_mover%27s_distance
Mahalonobis Distance
http://en.wikipedia.org/wiki/Mahalanobis_distance
PCA - Principle Component Analysis
http://en.wikipedia.org/wiki/Principal_component_analysis
SURF : Speed-up Robust Features (came after SIFT)
http://en.wikipedia.org/wiki/SURF
“A computational approach to determination of main subject regions in photographic images”
http://dx.doi.org/10.1016/j.imavis.2003.09.012
Integral Image
http://en.wikipedia.org/wiki/Summed_area_table
Haar Filters
http://en.wikipedia.org/wiki/Haar-like_features
Gradient Field.
http://en.wikipedia.org/wiki/Gradient
libsvm Support Vector Machine library
http://www.csie.ntu.edu.tw/~cjlin/libsvm/
AdaBoost
http://en.wikipedia.org/wiki/AdaBoost
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
http://www.cs.waikato.ac.nz/ml/weka/
AndreaMosaic - photo mosaic software (Windows)
23-Jan-2011
Electronic Imaging Conference. 23-27 Jan, 2011.
Edward Adelson
http://web.mit.edu/persci/people/adelson/
“Pictures are not taken in a vacuum--an overview of exploiting context for semantic scene content understanding” Signal Processing Magazine, IEEE
March 2006, Vol23 Issue 2.
Main subject detection. Belief map.
Duda, Hurt, and Storic. Statistical Pattern Recognition
http://amzn.com/0471056693
Earth Mover Distance
http://en.wikipedia.org/wiki/Earth_mover%27s_distance
Mahalonobis Distance
http://en.wikipedia.org/wiki/Mahalanobis_distance
PCA - Principle Component Analysis
http://en.wikipedia.org/wiki/Principal_component_analysis
SURF : Speed-up Robust Features (came after SIFT)
http://en.wikipedia.org/wiki/SURF
“A computational approach to determination of main subject regions in photographic images”
http://dx.doi.org/10.1016/j.imavis.2003.09.012
Integral Image
http://en.wikipedia.org/wiki/Summed_area_table
Haar Filters
http://en.wikipedia.org/wiki/Haar-like_features
Gradient Field.
http://en.wikipedia.org/wiki/Gradient
libsvm Support Vector Machine library
http://www.csie.ntu.edu.tw/~cjlin/libsvm/
AdaBoost
http://en.wikipedia.org/wiki/AdaBoost
Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
http://www.cs.waikato.ac.nz/ml/weka/
AndreaMosaic - photo mosaic software (Windows)
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