{"title":"Interactive Tangible Word Game","authors":"Chattraphon Pinkaew, Rattapoom Waranusast","doi":"10.1109/ICT-ISPC.2014.6923216","DOIUrl":null,"url":null,"abstract":"This study applies tangible user interface technology to develop “Interactive Tangible Word Game”. A user interacts with the game by placing plastic alphabetic characters on a surface and the game responds by projecting graphics on to the surface. The system uses the surface image and converts it to a binary image. Seven Hu's moments are then computed from each contour of each object in the image. These moments are compared with the stored character contours in order to find the most similar character. The recognized alphabetic characters are grouped into a word. If the word matches the projected picture, the user advances to the next word. Experimental results showed that the accuracy of the matching is 84%.","PeriodicalId":300460,"journal":{"name":"2014 Third ICT International Student Project Conference (ICT-ISPC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Third ICT International Student Project Conference (ICT-ISPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICT-ISPC.2014.6923216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study applies tangible user interface technology to develop “Interactive Tangible Word Game”. A user interacts with the game by placing plastic alphabetic characters on a surface and the game responds by projecting graphics on to the surface. The system uses the surface image and converts it to a binary image. Seven Hu's moments are then computed from each contour of each object in the image. These moments are compared with the stored character contours in order to find the most similar character. The recognized alphabetic characters are grouped into a word. If the word matches the projected picture, the user advances to the next word. Experimental results showed that the accuracy of the matching is 84%.