A. M. Rahma, Alipour Saeid, Muhsen J. Abdul Hussien
{"title":"虚拟数据集识别亚述楔形文字","authors":"A. M. Rahma, Alipour Saeid, Muhsen J. Abdul Hussien","doi":"10.1109/ICTA.2017.8336049","DOIUrl":null,"url":null,"abstract":"Cuneiform symbols represent a complex problem in pattern recognition, in particular for OCR (optical character recognition) due to challenges related to cuneiform-like character distortion and font heterogeneity. This paper proposes new approaches to recognise Assyrian cuneiform characters using OCR to classify the symbols. as a new way to recognize the Assyrian letters by dealing with symbols of complex character. The dataset utilised consists of 16 patterns to reflect all probabilities associated with each cuneiform symbol related to their shape and directions, assuming each character consists of a set of symbols. Polygon approximation techniques are used to generate feature vectors for the classification tasks. The proposed method obtains classification ratios up to 91% depending on the algorithm used for the feature vector.","PeriodicalId":129665,"journal":{"name":"2017 6th International Conference on Information and Communication Technology and Accessibility (ICTA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Recognize assyrian cuneiform characters by virtual dataset\",\"authors\":\"A. M. Rahma, Alipour Saeid, Muhsen J. Abdul Hussien\",\"doi\":\"10.1109/ICTA.2017.8336049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cuneiform symbols represent a complex problem in pattern recognition, in particular for OCR (optical character recognition) due to challenges related to cuneiform-like character distortion and font heterogeneity. This paper proposes new approaches to recognise Assyrian cuneiform characters using OCR to classify the symbols. as a new way to recognize the Assyrian letters by dealing with symbols of complex character. The dataset utilised consists of 16 patterns to reflect all probabilities associated with each cuneiform symbol related to their shape and directions, assuming each character consists of a set of symbols. Polygon approximation techniques are used to generate feature vectors for the classification tasks. The proposed method obtains classification ratios up to 91% depending on the algorithm used for the feature vector.\",\"PeriodicalId\":129665,\"journal\":{\"name\":\"2017 6th International Conference on Information and Communication Technology and Accessibility (ICTA)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 6th International Conference on Information and Communication Technology and Accessibility (ICTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTA.2017.8336049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th International Conference on Information and Communication Technology and Accessibility (ICTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTA.2017.8336049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognize assyrian cuneiform characters by virtual dataset
Cuneiform symbols represent a complex problem in pattern recognition, in particular for OCR (optical character recognition) due to challenges related to cuneiform-like character distortion and font heterogeneity. This paper proposes new approaches to recognise Assyrian cuneiform characters using OCR to classify the symbols. as a new way to recognize the Assyrian letters by dealing with symbols of complex character. The dataset utilised consists of 16 patterns to reflect all probabilities associated with each cuneiform symbol related to their shape and directions, assuming each character consists of a set of symbols. Polygon approximation techniques are used to generate feature vectors for the classification tasks. The proposed method obtains classification ratios up to 91% depending on the algorithm used for the feature vector.