(Association for Computing Machinery, Inc (ACM), 2017) Herrera-Camara, Jorge-Ivan; Hammond, Tracy; Holger Winnemoeller and Lyn Bartram
Flowcharts play an important role when learning to program by conveying algorithms graphically and making them easy to read and understand. Computer-based owchart design requires the user to learn the so ware rst, which o en results in a steep learning curve. Paper-drawn owcharts don't provide feedback. We propose a system that allows users to draw their owcharts directly on paper combined with a mobile phone app that takes a photo of the owchart, interprets it, and generates and executes the resulting code. Flow2Code uses o -line sketch recognition and computer vision algorithms to recognize owcharts drawn on paper. To gain practice and feedback with owcharts, the user needs only a pencil, white paper, and a mobile device. e paper describes a tested system and algorithmic model for recognizing and interpreting o ine owcharts as well as a novel geometric feature, Axis Aligned Score (AAS), that enables fast accurate recognition of various quadrilaterals.