Demograhphic anaylsis of handwritten task was an effort made by me for fulfilment of my bachelors degree.
Handwritings can be classified into many categories including gender, age, handedness, and nationality. This type of classification has several applications. For example, in the forensic domain, handwriting classification can help the investigators to focus on a certain category of suspects. Additionally, processing each category separately leads to improved results in writer identification and verification applications.
For classification, we have employed a feed forward artificial neural network. The features from writing samples of male and female writers in the training database are fed to the network making it learn to differentiate between the two classes. The number of hidden neurons in the network is chosen empirically using the validation dataset. During classification, the feature vector of the query writing image is
fed to the trained network which outputs the class label, i.e. male or female writer.
Unfortuantely this code is not packadged SORRY :(, for using you have to setup Matlab locally in your machine and perfect entry point for starting is via GUI class.