Analyzing Handwriting for Gender, Handedness and Combined Prediction using Machine Learning Algorithms

Studies related to the handwriting recognition has got good pace in recent time. Various research works were going on for recognition of handwriting in online and offline mode both. Manually recognition of handwriting is also an approach people are working on. A prediction based on the handwriting includes recognizing gender, age, handedness, behavior, basic human mood, nationality, ethnicity and many more. For this various predefined datasets are available. The available datasets are in many different languages. So fetching the required dataset of a particular language data is a tedious job to perform. In various other works the researchers had used different data as per their requirements. Here in this work of ours we are working with two different datasets. A new task that we had taken up here is we have created our own dataset. Thus here, the Machine learning algorithms were performed for predicting the traits firstly on IAM dataset of English data samples and another Real time dataset also in English writing scripts.