{"title":"Flow2Code: from hand-drawn flowcharts to code execution","authors":"Jorge Iván Herrera Cámara, T. Hammond","doi":"10.1145/3092907.3092909","DOIUrl":null,"url":null,"abstract":"Flowcharts play an important role when learning to program by conveying algorithms graphically and making them easy to read and understand. Computer-based flowchart design requires the user to learn the software first, which often results in a steep learning curve. Paper-drawn flowcharts don't provide feedback. We propose a system that allows users to draw their flowcharts directly on paper combined with a mobile phone app that takes a photo of the flowchart, interprets it, and generates and executes the resulting code. Flow2Code uses off-line sketch recognition and computer vision algorithms to recognize flowcharts drawn on paper. To gain practice and feedback with flowcharts, the user needs only a pencil, white paper, and a mobile device. The paper describes a tested system and algorithmic model for recognizing and interpreting offline flowcharts as well as a novel geometric feature, Axis Aligned Score (AAS), that enables fast accurate recognition of various quadrilaterals.","PeriodicalId":393945,"journal":{"name":"Proceedings of the Symposium on Sketch-Based Interfaces and Modeling","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Symposium on Sketch-Based Interfaces and Modeling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3092907.3092909","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Flowcharts play an important role when learning to program by conveying algorithms graphically and making them easy to read and understand. Computer-based flowchart design requires the user to learn the software first, which often results in a steep learning curve. Paper-drawn flowcharts don't provide feedback. We propose a system that allows users to draw their flowcharts directly on paper combined with a mobile phone app that takes a photo of the flowchart, interprets it, and generates and executes the resulting code. Flow2Code uses off-line sketch recognition and computer vision algorithms to recognize flowcharts drawn on paper. To gain practice and feedback with flowcharts, the user needs only a pencil, white paper, and a mobile device. The paper describes a tested system and algorithmic model for recognizing and interpreting offline flowcharts as well as a novel geometric feature, Axis Aligned Score (AAS), that enables fast accurate recognition of various quadrilaterals.