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Department of IT

WAVELET- BASED APPROACH TO CHARACTER SKELETON

MEMBERS:

GUIDE:

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PROBLEM STATEMENT

To implement a character skeletonization scheme which is effective in extracting relevant features of the character for optical character recognition(OCR), handwriting recognition, signature verification.

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ANALYSIS PHASE

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LITERATURE SURVEY

• Wavelet-based approach to character skeleton.

• Skeletonization of ribbon-like shapes based on new wavelet function.

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PROBLEMS TO OVERCOME

In traditional algorithms (Fourier Transform-FT and Symmetric axis transform-SAT),

• The symmetric center of skeleton was computed indirectly by measuring inscribed circle or the symmetric triangle.

• Moreover, the skeleton obtained slightly deviates from the center.

• Skeleton obtained is distorted by artifacts and branches.

• Cannot be applied to gray-level images

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WHAT IS CHARACTER SKELETON?

• The ‘skeleton’ of a character is the locus of the midpoints or the symmetric axis of the character stroke

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WHY WAVELET APPROACH?

• Wavelet transform is capable of providing the time and frequency information simultaneously.

• Modulus-maxima symmetric analysis technique to directly extract skeleton by contour line detection.

• Skeleton can be extracted more accurately based on wavelet based amendment processing.

• Robust against noise.

• Applicable to both binary and gray-level images.

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Department of IT

PROPOSED MODELIn our new wavelet-based approach ,these are the ideas

proposed to overcome the above problems,• The symmetric center can be determined as the midpoints

of the symmetric points directly using the new wavelet-based symmetry analysis method.

• A skeleton representation is robust against noise and insensitive to linear geometric transformations, such as translation, rotation, and scaling.

• The Amendment processing method of the proposed model plays an important role in effectively removing artifacts and distortions.

• Unlike the traditional pixel-based methods the proposed curve-based method is applicable to gray-level images too.

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USE-CASE DIAGRAM

Detect contour points and join them

user character recognition systemReduce noise by thresholding

Compute modulus of WT and gradient codes

Perform wavelet transform

Input the digitized character image

Amendment processing

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SYSTEM TEST PLAN

INPUTEnglish characters &numerical images

OUTPUTSkeleton of the Character stroke.

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DESIGN PHASE

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MODULES

There are two major modules, namely

1. Generating the new wavelet function, define the low-pass filter and wavelets.

2. Using the WLMMS technique, extracting the skeleton of the character stroke.

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EXTRACTION OF SKELETONIn this module,• A direct technique is used, where a new wavelet-based

symmetry analysis is developed to find the central line of the stroke.

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WAVELETS

• The wavelets imply the partial derivatives of a low pass filter

and

is chosen as

),(),(1 yxx

yx

),(),(2 yxy

yx

),( yx )( 22 yx

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ALGORITHM

• Input the digitized character image and select a suitable scale.

• Perform the wavelet transform to the character image.

• Compute modulus of the wavelet transform.• Remove the noise.• Compute local modulus maxima .• Find the symmetric pair of modulus maxima

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AMENDMENT PROCESSING

Here, the obtained skeleton of the character stroke is modified to remove spurs and artifacts so that the skeleton is accurate and relevant for recognition.

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UNIT TEST PLAN

• Unit 1- Primary Skeleton Extraction Unit In which a character image is inputted and the

primary skeleton of the regular region is obtained as output.

• Unit 2- Amendment Processing UnitIn which output of the unit 1 is used as input

and modified to obtain the final skeleton of the input image as output.

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DESIGN• The wavelet transform of the image is performed using the function

• The modulus of the WT is found using

and gradient direction with the help of

• For the noise removal, the threshold level chosen is 0.39.

2221 ),(),(|:),(| yxfWyxfWyxfW ssS

)),(),(tan(arg),( 1

2

yxfWyxfWyxfA

s

ss

),)(*(),)(*(),( 11 yxfx

syxfyxfW sss

),)(*(),)(*(),( 22 yxfy

syxfyxfW sss

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SOFTWARE AND HARDWARE

• SOFTWARE:Mat lab 7.0

• HARDWARE:3.0 GHz Pentium IV CPU1GB RAM

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SCREEN SHOTS

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ORIGINAL IMAGE

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GRADIENT DIRECTION IMAGE

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MODULUS MAXIMA IMAGE

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PRIMARY SKELETON

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FINAL SKELETON

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THANK YOU

Department of IT