Khmer ocr using gfd_seminar_day

Sovann EN

5th Year Engineering student

Dept. Computer Science & Communication

Institute of Technology of Cambodia

Phnom Penh, Cambodia

Khmer OCR System

1Khmer OCR System

Native of research work

• A collaboration work with Mr. Kruy Vanna, PhD A collaboration work with Mr. Kruy Vanna, PhD

student at kameyama Laboratory , GITS, Waseda student at kameyama Laboratory , GITS, Waseda

UniversityUniversity

• The Objective is to produce a reliable Khmer OCR The Objective is to produce a reliable Khmer OCR

system which is independent of Font and Sizesystem which is independent of Font and Size

2Khmer OCR System

Outline

• Overview of OCROverview of OCR

• Training dataTraining data

• Pre-processing and Segmentation Pre-processing and Segmentation

• features extraction and recognition processfeatures extraction and recognition process

• Post-processingPost-processing

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Outline

4Khmer OCR System



• Pre-processing and features extractionPre-processing and features extraction

• Training process and recognition systemTraining process and recognition system


What is OCR ???

• Optical Character Recognition (OCR) is the Optical Character Recognition (OCR) is the mechanical or electronic translation of scanned mechanical or electronic translation of scanned images of handwritten, typewritten or printed text images of handwritten, typewritten or printed text into machine-encoded textinto machine-encoded texthttp://en.wikipedia.org/wiki/Optical_character_recognitionhttp://en.wikipedia.org/wiki/Optical_character_recognition

5Khmer OCR System

• a document , a scan process , ocr system and an a document , a scan process , ocr system and an out put text. (put all these pictures here. Png out put text. (put all these pictures here. Png & .docx)& .docx)

Its applications…

Lister certaines applicationsLister certaines applications

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Overview of OCR System

Khmer OCR System7

Training data

Recognition system

(Knowledge)

Pre-processing

Features extraction

Input pattern

Character Reordering

Recognition result

Training processRecognition process Features

selection/reduction

Outline






8Khmer OCR System

Training Data

9Khmer OCR System

• To cover more font and size, it is necessary to To cover more font and size, it is necessary to

have more training sample of different font have more training sample of different font

Train Computer to recognize each of them is Train Computer to recognize each of them is ១១

Outline






10Khmer OCR System

Pre-processing and Segmentation

• Pre-processing aims to produce data that are Pre-processing aims to produce data that are

easy for the OCR systems to operate accuratelyeasy for the OCR systems to operate accurately

• The main objectives of pre-processing are :The main objectives of pre-processing are :• Binarization Binarization • Particle removalParticle removal

11Khmer OCR System

Binarization (Thresholding)

• Image linearization (thresholding) refers to the conversion of a gray-scale image into a binary image.

12Khmer OCR System

Particle removal

• Salt-and-pepper noise is a kind of noise which is Salt-and-pepper noise is a kind of noise which is

usually caused by small unnecessary dots usually caused by small unnecessary dots

produced by either the scanner or the source produced by either the scanner or the source

document itself.document itself.

13Khmer OCR System

Segmentation

• Segmentation aims to produce each component Segmentation aims to produce each component

to be recognized by the system. to be recognized by the system.

• The process is to separate the text of a page The process is to separate the text of a page

into each separate line, then to separate each into each separate line, then to separate each

line into Vertical Component, and finally produce line into Vertical Component, and finally produce

each independent symbol. each independent symbol.

14Khmer OCR System

Segmentation

• Segmentation aims to produce each component Segmentation aims to produce each component

to be recognized by the system. to be recognized by the system.

• The process is to separate the text of a page The process is to separate the text of a page

into each separate line, then to separate each into each separate line, then to separate each

line into Vertical Component, and finally produce line into Vertical Component, and finally produce

each independent symbol. each independent symbol.

15Khmer OCR System

Example using CCA

16Khmer OCR System

Feature Extraction & Recognition

• 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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Recognition Process

• GFD is derived by applying two-dimensional GFD is derived by applying two-dimensional

Fourier transform on a polar-raster sampled Fourier transform on a polar-raster sampled

shape image.shape image.

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Generic Fourier Descriptor

19Khmer OCR System

well…this is well…this is កាកា

GFD Feature vectorGFD Feature vector

well…this is well…this is កាកា

Recognition Process

20Khmer OCR System

???

Input imageInput image Training ImageTraining Image

Recognition Process

• The similarity between two shapes is measured The similarity between two shapes is measured

by the City-Block distance of the two feature by the City-Block distance of the two feature

vectors of the shape.vectors of the shape.

• The lower value means the more similar the The lower value means the more similar the

shapes are.shapes are.

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Post-processing : Reordering

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SegmentationSegmentation

Recognized wordRecognized word

ReorderingReordering

Experimental Result

23Khmer OCR System

precision

Recall

F-Mesure

• The test was conducted on a document with a The test was conducted on a document with a

resolution of 300 dpi of … symbols.resolution of 300 dpi of … symbols.

Khmer OCR Using Generic Fourier Descriptor Back

Thank for your attention !!!

24Khmer OCR System

Reference28


[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.

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Reference29


[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.

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Data & Analytics

Khmer ocr using gfd_seminar_day