Handwritten statement analysis using neural networks
Goldie Gabrani, Andrew Solomon, Utkarsh Dviwedi · 2016
This paper aims to scan a handwritten statement sample in the form of an image then uses the neural network to identify the graphological and statement analysis marker s that can give an insight into the psyche of the person who wrote the sample. It is a tried and tested fact that at least 70% of the communication that we engage in is nonverbal in nature. It is from this fact that the sciences of Micro-expression reading, body language analysis etc originated. A similar pattern is observed in the the linguistics of the choice of words of a person and his handwriting. Graphology (Handwriting Analysis) and Statement Analysis can also be a tool to gain an insight in to the psyche of the person. For example if a person uses the word never as a substitute for no in a yes or no there is a high probability of a suspicion of deception in the context. Similar techniques are used by experts of Neuro Linguistic programming worldwide for a variety of applications. They are used to interrogate criminals and hasten the process of investigation. They can act as human lie detectors. From a written statement they can highlight the possible statement that need cross-verification as they can spot graphological and statement analysis markers in them. But such people are few in number and it takes years and years of training to be at that skill level. Hence a software (Matlab application) is then programmed to replicate this behaviour.