Sunday, January 30, 2011

Document Recognition and Retrieval. Electronic Imaging Conference. 27-Jan-2011

"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

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

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

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

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

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

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)