Personality is a combination of various characteristics and qualities of an individual. It may be affected by the growth and evolution of one’s values, attributes, relationships with the community, personal memories of life events, habits, and skills. Behaviours and decisions of an individual are largely directed by his/her personality. Identification of such a personality trait can be performed based on an individual’s handwriting features. Handwriting may be unique for each person and a person’s nature, behaviour, and certain psychological aspects can be inferred based on it. It is introduced as the field of graphology, also called graphoanalysis, to analyze personality based on handwriting. We perceived that many researchers have worked on personality and/or behaviour identification based on handwriting, however, most of them were limited to a few numbers of features. According to graphology, there is a vast range of features of handwriting strokes which carry psychological characteristics of the writer. In this survey, we present links between handwriting and personality psychology and examine different mechanisms for features extraction to predict a writer’s personality. Psychologically supported handwriting features help to understand personality traits. The paper relates these features and encourages the use of computer-based graphology for personality prediction. It also discusses applications of graphology in various fields.

Survey on handwriting-based personality trait identification

Personality Assessment is an emerging research area. In recent years, the interest of the scientific community towards personality assessment has grown incredibly. Personality is a psychological model that can be used to explain the wide variety of human behaviors with the help of individual characteristics. The applications of personality assessment range from behavior analysis to disease diagnosis, counseling, employee recruitment, social network analysis, security systems, mood prediction, and many others. Automatic personality assessment consists of the automatic classification of users' personality traits from the data such as video, speech and text. Despite growing number of works in personality assessment, it is still very difficult to say what the current state-of-the-art is. The objective of this survey paper is to discuss various approaches used for personality assessment and to present current state-of-art related to it. It also provides guidelines for further research.

Automatic personality assessment: A systematic review

The richest information about different emotional states and thinking styles of the person is carried by signature The signature analysis is one of the most effective and reliable indicator for prediction of personality. As it reveals the true personality which includes fears, honesty and many other individual personality traits. This can happen with the help of few features like underscores below signature, appearance of dot on the letter, curved start, ending stroke, and streaks disconnected. This paper is focused on above mentioned features. The database has 60 signatures of 10 different persons with 6 samples of each and is properly scanned at 500dpi resolution scanner. The performance is evaluated by splitting a signature into five categories-left, right, upper, middle and bottom. An artificial neural network and structural identification algorithm is used for the prediction of personality and the obtained accuracy rate is 100%, 95%, 94%, 96% and 92% respectively The significance of work is to reveal personality traits in criminology, medical science and counseling.

Analysis of signature for the prediction of personality traits

Handwriting analysis is an approach to modeling human activities are to judge the human as a device with a large number of internal mental states which they have. The research builds on the observation that although human behaviors such as handwriting, speech, hand gestures and even American Sign Language. Handwriting work as an indicator, which indicates personality and behavior of humans, for example, recruitment, interviewing and selection, team-building, counseling, and career-planning. The need of human personality recognition is more important in the modern word. Through this human can simplify their jobs and they are able to solve typical problems. Handwriting analysis or Graphology both are the scientific scheme of identifying, recognizing and distinguish behavior over the movements and patterns inform with the handwriting. During the ancient Indian civilization, it (handwriting analysis) was very common to identify the human behavior. In Graphology, handwriting process is analyzed through structural graphic elements in which the order to derive information about the writer's personality.

A survey on human personality identification on the basis of handwriting using ANN

Studies in psychology showed a close link between handwriting and personality, but this was never formally analyzed. In the context of career development there is a need to determine the personality type in a more efficient manner than the classic questionnaire. Moreover, in the fields of psychology and medicine, constant monitoring the patient's personality can provide information regarding his mental health status, if he suffers from mental disorders or show psychological symptoms for common physical diseases. We analyze the link between personality types and handwriting, by correlating the handwriting features with the personality primitives in a neural-network 3-level architecture. Results show an accuracy of 86.7% in determining the personality type, with highest accuracies for Extravert vs. Introvert and Thinking vs. Feeling personality primitives. The system computes the personality type in less than 1 minute, proving to be more efficient than a questionnaire and suitable for real-life use.

Study on determining the Myers-Briggs personality type based on individual's handwriting

Handwriting stroke reflects the written trace of each individual's rhythm and style. By examining all elements of handwriting and interpreting them separately or integrated, we could generate a sketch of the writer's character traits, emotional disposition and social style using standard of graphology. As image, the analysis of graphology is divided into two approaches that graphics features and segmentation digit each character. In this research, using combination of graphical approach based on signature and digit of character of application form using multi-structure algorithms and artificial neural networks (ANN). The image split into two areas: the signature based on nine features and application form of letters digit area. Each area had preprocessing performed to improve the recognition accuracy. Signature area is classified using ANN based on five features which result an accuracy of 5678%. While four feature of the signature that detection using multi structure algorithm result 87-100% accuracy. In meantime, pattern recognition of application form digit area using Learning Vector Quantization gave 43% accuracy. It used 100 sets of data testing after training with 10-25 data. The system has been implemented with the software so that it can be used for classification of personality from handwriting scanned automatically.

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Jeri Saputra

Papers

Recognition of Handwriting Based on Signature and Digit of Character Using Multiple of Artificial Neural Networks in Personality Identification