Pen Stroke Extraction and Refinement using Learned Models

Abstract

This paper presents a smart interface that automatically extracts and refines pen strokes from images of hand drawn sketches. The interface allows users to digitize hand-drawn material such sketches of flowcharts, cartoons or other pen based drawings and automatically isolate and refine the individual strokes making up the sketch. First, we present a method for extracting pen strokes based on learned constraints on curves. The approach consists of using a training set that shows good examples of curves and how a user would draw them. Given an image of a hand-drawn sketch, the system selects the pen stroke that is most statistically consistent with the examples in the training set and ranks the others based on their likelihood. Users can keep the selected candidate or they may scroll through the other top candidates to select a preferred solution. Second, we present an overview of our refinement procedure and its application on the extracted pen strokes. Using the same database of examples, the extracted pen stroke is refined to make it 'look' more like those in the database.