Khmer ocr using gfd
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Transcript of Khmer ocr using gfd
Mr. Sovann EN
5th Year Engineering student
Dept. Computer Science & Communication
Institute of Technology of Cambodia
Phnom Penh, Cambodia
Khmer OCR Using Generic Fourier Descriptor
Content
Khmer OCR Using Generic Fourier Descriptor
2
Introduction
Khmer OCR System Pre-processing
Segmentation
Feature Extraction
Recognition Process
Generic Fourier Descriptor In detail
Future work
Introduction
Optical Character Recognition (OCR) is the
electronic conversion of scanned images into
machine-encoded text.
OCR makes it possible to edit the text, to search for
a word or a phrase, to display or to print a copy free of
scanning artifacts and so on.
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Khmer OCR Using Generic Fourier Descriptor Back
Introduction
The ideas started prior to World War II.
Throughout the years, many reliable commercial and
academic prototypes have been developed in many
natural languages.
Still, due to the lacked effort in Khmer OCR, there
is no reliable Khmer OCR software.
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Khmer OCR Using Generic Fourier Descriptor Back
Introduction
The ideas started prior to World War II.
Throughout the years, many reliable commercial and
academic prototypes have been developed in many
natural languages.
Still, due to the lacked effort in Khmer OCR, there
is no reliable Khmer OCR software.
5
Khmer OCR Using Generic Fourier Descriptor Back
Introduction
The ideas started prior to World War II.
Throughout the years, many reliable commercial and
academic prototypes have been developed in many
natural languages.
Still, due to the lacked effort in Khmer OCR, there
is no reliable Khmer OCR software.
6
Khmer OCR Using Generic Fourier Descriptor Back
Introduction7
Khmer OCR Using Generic Fourier Descriptor Back
The current system is based on Mr. Vanna Kruy’s
work for his master degree at Waseda University.
The Objective is to produce a reliable Khmer OCR
system which is independent of Font and Size.
Khmer OCR System
Khmer OCR Using Generic Fourier Descriptor
OCR System consist of four majors stages :
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Pre-processing Segmentation Feature Extraction Post processing
Pre-processing
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Pre-processing aims to produce data that are easy
for the OCR systems to operate accurately. The main objectives of pre-processing are :
Binarization Noise removal
Binarization10
Image linearization (thresholding) refers to the
conversion of a gray-scale image into a binary image.
Khmer OCR Using Generic Fourier Descriptor
Binarization of Input Image
Salt-Pepper Noise removal11
Salt-and-pepper noise is a kind of noise which is
usually caused by small unnecessary dots produced by
either the scanner or the source document itself.
Khmer OCR Using Generic Fourier Descriptor Back
Particle removal
Segmentation12
Segmentation aims to produce each component to
be recognized by the system.
The process is to separate the text of a page into
each separate line, then to separate each line into
Vertical Component, and finally produce each
independent symbol.
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Connected Component Analysis13
Connected Component is a group of pixels
accumulating together to form a shape.
The process is to separate the text of a page into
each separate line, then to separate each line into
Vertical Component, and finally produce each
independent symbol.
Khmer OCR Using Generic Fourier Descriptor Back
14Example using CCA
Khmer OCR Using Generic Fourier Descriptor Back
Word Segmentation using CCA
15Example using CCA
Main part :
Sup script :
Sub script :
Ccdown :
Khmer OCR Using Generic Fourier Descriptor Back
Feature extraction16
In feature extraction stage, each character is
represented as a feature vector which becomes its
identity.
The major goal of feature extraction is to extract a
set of features which maximizes the recognition rate
with the least amount of elements.
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Generic Fourier Descriptor
Khmer OCR Using Generic Fourier Descriptor
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GFD is derived by applying two-dimensional
Fourier transform on a polar-raster sampled shape
image.
Polar-raster sampled : the image obtained after
circularly sampling an object in an image up to itsmaximum radius.
Example of GFD18
Khmer OCR Using Generic Fourier Descriptor Back
The similarity between two shapes are measured
by the city block distance between the two set of
GFDs.
រ្�khmer OS UI font and its GFD
Recognition Process19
Khmer OCR Using Generic Fourier Descriptor Back
To recognize, we compare the GFD’s score The score is obtain by comparing the CCs features
vector with CCs feature in database.
Recognition Process : Score20
Khmer OCR Using Generic Fourier Descriptor Back
The similarity between two shapes is measured by
the City-Block distance of the two feature vectors of
the shape.
The lower value means the more similar the shapes
are.
Generic Fourier Descriptor In detail
Khmer OCR Using Generic Fourier Descriptor
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GFD is derived by applying two-dimensional
Fourier transform on a polar-raster sampled shape
image.
A region-base shape descriptor proposed by
Dengsheng Zhang & Guojun Lu. It is confirm to
outperforms common contour-based and region-based
shape descriptors.
Algorithm to computer GFD
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Input the binary shape image data f(x, y) Get centroid of the shape (xc, yc) Set the centroid as the origin Compute Polar Fourier Transform Calculate Fourier Descriptor Output GFD
Polar Transform23
It is the transforming into polar image f(r, θ), for an
input image f(x, y).
c
ccc xx
yyyyxxr
arctan,)()( 22
1
0
1
0
1and
1where
M
yc
N
xc y
Nyx
Mx
shapetheof(barycent)centroidofrcoordinatotheis),( cc yx
Khmer OCR Using Generic Fourier Descriptor Back
Polar Raster Grid24
Polar raster sampling
Polar image Polar raster sample image in Cartesian space
Khmer OCR Using Generic Fourier Descriptor Back
Polar Raster Grid25
Binary polar raster sample shape images
Khmer OCR Using Generic Fourier Descriptor Back
Shape, shape normalization and its polar transform
2D- Fourier Transform26
2-D Fourier transform on polar raster sample
image f(r, ):
where 0r<R and i = i(2/T) (0 i<T); 0<R,
0<T. R and T are the radial frequency resolution
and angular frequency resolution respectively.
r i
i T
i
R
rjrfPF )]
2(2exp[),(),(
Khmer OCR Using Generic Fourier Descriptor Back
Normalization27
Translation invariant due to using centroid as
origin.
Scale normalization is archived due to the
proportional equality:
}|)0,0(|
|),(|,...,
|)0,0(|
|)0,(|,...,
|)0,0(|
|),0(|,...,
|)0,0(|
|)1,0(|,
|)0,0(|{
PF
nmPF
PF
mPF
PF
nPF
PF
PF
area
PFGFD
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Future Work28
Integrate GFD into the system Exploit the possibility to improve the accuracy by
using Classifier for Training module
Khmer OCR Using Generic Fourier Descriptor Back
Khmer OCR Using Generic Fourier Descriptor Back
Thank for your attention !!!
Reference30
Khmer OCR Using Generic Fourier Descriptor Back
[1] V. Kruy. Preliminary Experiment on Khmer OCR. Kameyama Laboratory, Waseda Univerisy, Japan.
[2] Thesis for master degree, Khmer OCR, Vanna Kruy.
[3] D. Zhang and G. Lu. Shape-based image retrieval using generic Fourier descriptor. Gippsland School of Computing and InformationTechnology. Monash University. Churchill, Victoria 3842, Australia.
[4] Thesis for Doctoral Degree, chapter 6: Generic Fourier Descriptor, Dengsheng Zhang.
[5] J.C.Rupe. Vision-Based Hand Shape Identification for Sign Language Recognition. Department of Computer Engineering Kate Gleason College of Engineering Rochester Institute of Technology Rochester, NY.
Reference31
Khmer OCR Using Generic Fourier Descriptor Back
[6] D. Dimov. A polar-Fourier-Wavelet’s Transform for Effective CBIR. 3rd ADBIS workshop on Data mining & Knowledge Discovery
[7] I. Lengieng, K. Sochenda and C. Sokhour. , Khmer OCR for Limon R1 Size 22 Report, PAN Localization Cambodia (PLC) of IDRC.er OCR
[8] A. Averbuch, R.R. Coifmany , D.L. Donohoz M. Eladx M. Israeli. Fast and Accurate Polar Fourier Transform. Department of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel. Department of mathematics, Yale University, New Haven CT 06520-8283 USADepartment of Statistics, Stanford University, Stanford 94305-9025 CA. USA.