Personality Detection using Handwriting Analysis Review

Hemlata,; Sachan, Manoj Kumar; Singh, Shailendra Kumar

doi:10.15224/978-1-63248-157-3-33

Cited by 17 publications

(7 citation statements)

References 5 publications

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“…The major objective of the proposed work is to overcome the disadvantages that exists in the prediction model using handwritten statements where multiple formats are not present is any existing models ( 1 – 29 ). In addition, only occasional treatments are provided for predicting depression with low complexity algorithms.…”

Section: Literature Surveymentioning

confidence: 99%

“…Teenage pupils who are experiencing depression have significant problems carrying out daily tasks and performing in various situations. According to a poll ( 1 ) more than 21% of teenagers in India reported suffering from serious depression in the previous year. Friendships and emotional bonds between families and friends are harmed by depression.…”

Section: Introductionmentioning

confidence: 99%

“…As a result of this, suicidal thoughts and attempts may result. Handwriting analysis, video and audio analysis, gesture and movement analysis, and psychological evaluation are among the many different approaches for detecting depression and other mental illnesses that might be created utilizing machine learning (ML) and deep learning methodologies ( 1 ). Depression is also one of the primary causes of the disability in teens.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Perception Exploration on Robustness Syndromes With Pre-processing Entities Using Machine Learning Algorithm

Kshirsagar

Manoharan²,

Shitharth

et al. 2022

Front. Public Health

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The majority of the current-generation individuals all around the world are dealing with a variety of health-related issues. The most common cause of health problems has been found as depression, which is caused by intellectual difficulties. However, most people are unable to recognize such occurrences in them, and no procedures for discriminating them from normal people have been created so far. Even some advanced technologies do not support distinct classes of individuals as language writing skills vary greatly across numerous places, making the central operations cumbersome. As a result, the primary goal of the proposed research is to create a unique model that can detect a variety of diseases in humans, thereby averting a high level of depression. A machine learning method known as the Convolutional Neural Network (CNN) model has been included into this evolutionary process for extracting numerous features in three distinct units. The CNN also detects early-stage problems since it accepts input in the form of writing and sketching, both of which are turned to images. Furthermore, with this sort of image emotion analysis, ordinary reactions may be easily differentiated, resulting in more accurate prediction results. The characteristics such as reference line, tilt, length, edge, constraint, alignment, separation, and sectors are analyzed to test the usefulness of CNN for recognizing abnormalities, and the extracted features provide an enhanced value of around 74%higher than the conventional models.

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Section: Literature Surveymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Perception Exploration on Robustness Syndromes With Pre-processing Entities Using Machine Learning Algorithm

Kshirsagar

Manoharan²,

Shitharth

et al. 2022

Front. Public Health

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show abstract

“…Feature extraction is a process of dimensionality reduction (extraction data) from high dimensional input data [28]. The output data is used for analyzing human personality.…”

Section: Feature Extraction On Handwriting Analysismentioning

confidence: 99%

Automated handwriting analysis based on pattern recognition: a survey

Samsuryadi¹,

Kurniawan²,

Mohamad³

2021

IJEECS

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<span>Handwriting analysis has wide scopes include recruitment, medical diagnosis, forensic, psychology, and human-computer interaction. Computerized handwriting analysis makes it easy to recognize human personality and can help graphologists to understand and identify it. The features of handwriting use as input to classify a person’s personality traits. This paper discusses a pattern recognition point of view, in which different stages are described. The stages of study are data collection and pre-processing technique, feature extraction with associated personality characteristics, and the classification model. Therefore, the purpose of this paper is to present a review of the methods and their achievements used in various stages of a pattern recognition system. </span>

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“…So later on the computer aided methods has been used to recognize the handwriting pattern and behavior of human. Handwriting analysis is one if the technique to predict the human personality including behavior, anger, self-esteem, honesty, fears and so on [1]. Different parameters of personality trait has been taken such as baseline, slant, margin, width and so on as the input to the machine learning methods and gives output in the form of personality trait.…”

Section: Introductionmentioning

confidence: 99%

Handwriting Recognition by Machine Learning

2019

IJITEE

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Handwriting is one of the most natural ways of communication among people. The handwriting recognition task is the main concern of scientific community because handwriting can be varies with the same person or from one person to another hence the prediction of human behavior through handwriting is a complex task. Earlier the handwriting analysis has been done by graphologists but due to the modernization and the arrival of digital world the handwriting analysis can be done with the help of computer aided machines. Different software and algorithms has been defined to do the analysis. In the new world of machine learning handwriting recognition and the prediction of human behavior can be done by using different techniques of machine learning which increase the speed of analysis This paper studies the recent advances and the trends in the field of handwriting recognition by machine learning

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Personality Detection using Handwriting Analysis Review

Cited by 17 publications

References 5 publications

Perception Exploration on Robustness Syndromes With Pre-processing Entities Using Machine Learning Algorithm

Perception Exploration on Robustness Syndromes With Pre-processing Entities Using Machine Learning Algorithm

Automated handwriting analysis based on pattern recognition: a survey

Handwriting Recognition by Machine Learning

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