MAJOR PROJECT

Submitted by:-Aanchal Khandelwal (10103600)

Manvi Garg (10103622)

INTRODUCTIONYour brain guides your hand. Everything put

on paper is a result of a two-way circuit between your brain and the motor reflex muscles of your hand.

In our Project we are analyzing the handwriting of individual to depict the personality of that person.

Handwriting becomes a Polygraph or Oscilloscope read-out of your "complete self."

To you, it's just handwriting, but to a handwriting analyst, it paints a picture of the person "behind the pen."

Handwriting Analysis- What is it?

I know it seems impossible, but a trained graphologist and by using today’s technology it is possible we can gather an astonishing amount of information about the writer just from analyzing their handwriting.

Besides creating a complete personality profile, many other things are revealed in your handwriting, such as health issues, morality, past experiences, hidden talents, mental problems-- to name just a few.

Handwriting analysis, or graphology, is the science involved in producing a personality profile of the writer by examining the characteristics, traits and strokes of an individual's handwriting.

PROJECT Prediction of Personality by handwriting analysis.

Every individual have different style of writing as his/her brain have different ways to show what’s going on in his mind so we came across with a idea to make this project.

One can easily give the digital sample of his/her handwriting to a computer and it calculates the features using the image processing techniques and predicts the nature of the writer.

To make this computerized we considered Different types

of features and studied them thoroughlyWe used python as our platform.

Allograph and allograph combination analysis is a scientific method of writer identification and evaluating the behaviour.

To make this computerized we considered six main different types of features:

(I ) size of letters (II ) slant of letters and words (III ) baseline (IV) pen pressure (V) spacing between letters ( VI ) spacing between words in a document to identify the personality of the writer.

Segmentation is used to calculate the features from digital handwriting in which the letters or words are segmented using image processing and applying various steps.

Handwriting image is uploaded by the user or individual and then the image is processed .

Research analysisS.NO.

WRITING CATEGORIES

PERSONALITY BEHAVIOUR

1 LARGE LETTERS Likes being noticed, stands out in crowd

2 SMALL LETTERS Introspective, not seeking attention, modest

3 MEDIUM LETTERS Adaptable, fits into a crowd, practical, balanced

4 RIGHT SLANT Sociable, responsive, interested in others, friendly

5 LEFT SLANT Reserved , observant , self-reliant

6 VERTICAL Practical , independent, controlled ,

7 LIGHT PEN PRESSURE

Strong emotion , successful, emotion last for long time

8 HEAVY PEN PRESSURE

Try to avoid energy draining situations

9 FAR SPACING LETTERS

Openness of sentiment and intelligence

10 CLOSE SPACING LETTER

Closeness of sentiment and intelligence

11 FAR SPACING WORDS Give me breathing space

12 CLOSE SPACING WORDS

Wish to be with others , intrusive

13 RAISING BASELINES Optimistic, upbeat, positive attitude

14 FALLING BASELINES Tired , overwhelmed , pessimistic , not hopeful

Psychological personality traits predicted by various handwriting styles of writer.

1. A writer with heavy pressure and a vertical slant.Heavy pressure= strong emotions and vertical slant= trying to hold emotions back. This writer is usually the one who keeps his wits about him. When "all hell breaks loose," his head rules. He will not be as emotionally responsive as a right slant writer and will "keep cool". This "heavy pressure-vertical slant" writer won't be able to keep his cool all of the time. When his emotions get the best of him he may "fly off the handle" at unpredictable times.

2. A person with light pressure writing (not much emotional or physical energy) and a left slant (tries to avoid emotional situations). This person will be emotionally withdrawn, cold, indifferent and self centred .

There are many steps involved in creating a complete personality profile. Using these first two steps you can begin to put together your own "profile" which can be useful in both personal and professional relationships.

Now let's mix some of these traits and see what we come up with.

How we do it ?We follow certain steps to reach our goalFirst an image is uploaded by the user it should be on

plain paper and should be in writers handwriting only.To get the good result we need a good image or by

using threshold we remove the noise from the image now as the image is free from noise it can be looked upon further .

Now image is pre-processed and using image processing techniques we will segment the images in different parts first we will segment the image in word and then we will segment each character of image this will give extra area to look on the nature of the person personality

Now as the image is segmented and we have every character in the image we would now extract the different outputs from the image we would check each feature. We would check slant in the letters i.e they are slanted right or left or vertical. We would check the baseline angle of the lines in the image are these lines straight that means whether person right in straight line or not. Now after checking other pre specified features we would come with the result of the person personality. Image processing play a crucial role in the project as it help us to get the segmented part of the image. These segmented parts of the image are the basic of what we actually need.

Segmentation is used to calculate the features from digital handwriting, contour selection and canny is used to select the outlines of words and edges of lines. Finally, all extracted features are fed to svm and ann which outputs the behaviour of the writer. The proposed method tells us that which method is efficient and effective with the actual real graphology method.

SVMsupport vector machines are 

supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis.

We used RBF to give input to the SVM basically SVM take input as a function .

SVM give the better result and Exact result as compared to the ANN

RBFA radial basis function (RBF) is a real-

valued function whose value depends only on the distance from the origin

Sums of radial basis functions are typically used to approximate given functions . This approximation process can also be interpreted as a simple kind of neural network. RBFs are also used as a kernel in support vector classification.

Books for Handwriting Analysis

It revelsYour PersonalityYour emotionsYour likes and dislikesYour Strengths and

weaknessYour intellect and much

more.

Tools , Platform & Software neededFor our project we need python 2.7 and

aboveOperating system may be windows or Ubuntu

or any other Operating system supporting Python

Other library used in the project are Numpy - Number Python , a powerful N dimensional array object.Open CV- library for image processing

Mat lib- Mat plot library. My sql db- used to connect to database.

Novelty/benefitsTo make this computerized this we considered

few old and some new features to handwriting analysis:

size of letters, baseline, slant angle of letters to the baseline, word spacing

Dots of I’s, loops of y ’s and f ’s , height of T-bars in a document to identify the personality of the writer. For extracting the features we used various functionality and processes.

Benefits: With increase no. of features, we will get

better results and effective. Also, on comparing two classifier output, we’ll

see that which classifier is better in terms of efficiency and matched to real world scenarios.

We’ll check the compatibility between two people, so it going to tell they are good for team work or not.

We can check that if a person is able to handle pressure or not in case of difficult situation.

Future Scope

It would be proved to be good application for those psychologists and doctors who want to treat their patient and predict their basic nature and how it can be improved.

It can be used for employees, so we can see their particulars interests so we‘ll get benefits from their talents.

We’ll calculate the average width and height of letters of a person’s handwriting, and compare the result with other persons.

We can send handwriting analysis of the person to their phone so that person can get his information any time.

References 1. Shitala Prasad, Vivek Kumar Singh, Akshay Sapre “Handwriting Analysis based on Segmentation Method for

Prediction of Human Personality using Support Vector Machine”, International Journal of Computer Applications, Volume 8– No.12, October 2010.

2.Abdul Rahiman M,Diana Varghese,Manoj Kumar G “HABIT:Handwritten Analysis Based Individualistic Traits Prediction”, International Journal of Image Processings, Volume 7, October 2013.

3.Perut Boribalburephan and Boonnatee Sakboonyarat , “An Algorithm Development for Handwritten Character Recognition by Personal Handwriting Identity Analysis [PHIA]”, Knowledge and Smart Technology(KST),2012 4TH International Conference, Pages 6-10.

4.Abedelkadir Asi,Raid Saabni and Jihad El-Sana, “Text Line Segmentation for Gray Scale Historical Document Images”Workshop on Hstorical Document Iaging and processing pages 120-126,2011.

5.Pankaj kumawat,asha khatri,baluram nagaria, “Comparative analysis of offline handwriting recognition using invariant moments with HMM and combined SVM-HMM classifier”, Communication systems and network technologies(CSNT),2013 international conference pages 140-143,2013.

6.Vassilis papavassiliou,themos stafylakis,george carayannis, “Handwritten document image segmentation into text lines and words.”, Volume 43,issue 1,pages 369-377,2009.

7.Champa H N,K R AnandaKumar, “Automated Human Behavior Prediction through Handwriting Analysis” , Procedings in integrated intelligent computing(ICIIC),2010 FIRST INTERNATIONAL CONFERENCE,PAGES 160-165, 2010.

8.Tal Steinherz, David Doermann, Senior Member, IEEE, Ehud Rivlin, Member, IEEE, and Nathan Intrator, “Offline Loop Investigation for Handwriting Analysis”, IEEE Transactions on pattern analysis and machine intelligence, vol 31, no.2, 2009

[9] Champa H N, Dr. K R AnandaKumar, “Artificial Neural Network for Human Behavior Prediction through Handwriting Analysis” , International Journal of Computer Applications (0975 – 8887) Volume 2 – No.2, May 2010.

[10] Tristan Wright, “Handwriting Recognition with Artificial Neural Networks and Open CV”. [11] D. John Antony, O.F.M.Capp, “Personality Profile Through Handwriting Analysis” , A Textbook of Handwriting

Analysis : Anugraha Publications, Anugraha (Tamil Nadu Capuchin Institute for Counselling, Psychotherapy and Research), September 2008