Wen-Yuan Chen, Sheng-yuan Heish, Chiu-Yu Yen, Dang-Yi Kuo
{"title":"The Chinese-chess image identification techniques on spatial domain","authors":"Wen-Yuan Chen, Sheng-yuan Heish, Chiu-Yu Yen, Dang-Yi Kuo","doi":"10.1109/WCICA.2011.5970660","DOIUrl":null,"url":null,"abstract":"In this paper, we develop a feature measure method of the chess object from a chess image and identify the chess by using the features. Features are generated by calculating the distance between the contour of the character and the center of the chess object. We compare the features of input chess image with the standard database chess image to obtain a corrected chess identification results. There are two advantages compare with other methods: 1) Our method is robust from the 40 incline degree test. 2) Our method can resist the 20% pepper and salt noise attacks. In order to demonstrate the effectiveness of the proposed scheme, simulations under all kinds of various conditions were conducted. The experimental results show that our proposed scheme can exactly identify chess images 100% of the time.","PeriodicalId":211049,"journal":{"name":"2011 9th World Congress on Intelligent Control and Automation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 9th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2011.5970660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, we develop a feature measure method of the chess object from a chess image and identify the chess by using the features. Features are generated by calculating the distance between the contour of the character and the center of the chess object. We compare the features of input chess image with the standard database chess image to obtain a corrected chess identification results. There are two advantages compare with other methods: 1) Our method is robust from the 40 incline degree test. 2) Our method can resist the 20% pepper and salt noise attacks. In order to demonstrate the effectiveness of the proposed scheme, simulations under all kinds of various conditions were conducted. The experimental results show that our proposed scheme can exactly identify chess images 100% of the time.