Online Recognition of Outlines in Teeline Shorthand Language

Abstract

To summarize the speech delivered by the VIPs in the short time the short hand newlinelanguage is employed. Mainly there are two most popularly used shorthand languages namely newlinePitman and Teeline. An automatic shorthand language recognition system is essential in order newlineto make use of the handheld devices for speedy conversion to the native English language. To newlineaddress the above issue we had attempted the system in this thesis using the three methods, newlinefirstly using the Finite Automata, using the machine learning approaches and lastly using the newlineDeep learning (CNN). The method involves collecting the input image, preprocessing, newlinesubtracting the context to the grayscale image, extracting the features and applying them to newlinethe classifier or directly giving the Deep Learning images for English letter prediction. newlineAny of the pattern recognition system starts with the data collection step, an android newlineapplication along with the digital pen iball8060U is interfaced to extract the data drawn from newlinethe user. Considered the 45 to 50 different writers to generate the data. The study reviles that newlinethe data generation becomes considerably well as user became familiar with the application newlineand digital pen. The android application allows the user to write the alphabets in the provided newlinetemplate space only. The 10,600 dataset has been generated in it 60% is reserved for training, newline20% of dataset is reserved for testing and validation. newlineThe handwriting process is documented by the acquisition system as a stream of (X, newlineY) coordinates with the correct pen position sensor and pen-up / pen-down switching. No newlinepressure level was reported. The dataset distribution consists of 53 files (one for each author) newlineand a file for data collection. This file contains descriptions of the Id (ID), the name of the newlinecharacter (Label) and the specific type (Char). The stroke information is collected in order to newlinerecognize the behavior of the Finite State Automata. newlineThe generated dataset is used to extract the feret features from each image reserved newlinefor