Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis

A method for automatically assessing the constructional sequence from a neuropsychological drawing task using Hidden Markov Models is presented. We also present a method of extracting and identifying the position of individual pen strokes relating to individual sides of a shape within a drawing to form training and testing sequences. Our results from two experiments using data from patients with visuo-spatial neglect show the HMM classifier is able to generalise on incorrectly extracted sequences and obtain a diagnostic classification which can be used alongside other forms of conventional assessment.

• Type: Conference
• Year: 2003
• Where: ICDAR
• Authors: Richard M. Guest, Samuel Chindaro, Michael C. Fairhurst, Jonathan M. Potter
• Keywords: Document Analysis, Hidden Markov Models, ICDAR 2003, Individual Pen Strokes, Neuropsychological Drawing Task