F. Fitrianingsih, Diana Tri Susetianingtias, Dody Pernadi, Eka Patriya, Rini Arianty
{"title":"人工神经网络在脱机手写体图像识别中的实现","authors":"F. Fitrianingsih, Diana Tri Susetianingtias, Dody Pernadi, Eka Patriya, Rini Arianty","doi":"10.33096/ilkom.v14i1.1113.63-73","DOIUrl":null,"url":null,"abstract":"Data produced Segmentation was done using and contours. The modeling was carried out using and hard. The recognition model used the The results of the study are to be to Abstract Identifying a writing is an easy thing to do for human, but this does not apply to computers, in particular if it is handwriting. Handwriting recognition, especially cursive handwriting is a research in the area of image processing and pattern matching that is challenging to complete, following the different characteristics of each person's cursive handwriting style. In this study, the use of the ANN model will be implemented in performing offline handwriting image recognition. The cursive handwriting image that has been obtained is then preprocessed and segmented using bounding box rectangle and contour techniques. Evaluation of system performance using global performance metrics in this study resulted in a percentage of 93% where the","PeriodicalId":33690,"journal":{"name":"Ilkom Jurnal Ilmiah","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The Implementation of Artificial Neural Network (ANN) on Offline Cursive Handwriting Image Recognition\",\"authors\":\"F. Fitrianingsih, Diana Tri Susetianingtias, Dody Pernadi, Eka Patriya, Rini Arianty\",\"doi\":\"10.33096/ilkom.v14i1.1113.63-73\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data produced Segmentation was done using and contours. The modeling was carried out using and hard. The recognition model used the The results of the study are to be to Abstract Identifying a writing is an easy thing to do for human, but this does not apply to computers, in particular if it is handwriting. Handwriting recognition, especially cursive handwriting is a research in the area of image processing and pattern matching that is challenging to complete, following the different characteristics of each person's cursive handwriting style. In this study, the use of the ANN model will be implemented in performing offline handwriting image recognition. The cursive handwriting image that has been obtained is then preprocessed and segmented using bounding box rectangle and contour techniques. Evaluation of system performance using global performance metrics in this study resulted in a percentage of 93% where the\",\"PeriodicalId\":33690,\"journal\":{\"name\":\"Ilkom Jurnal Ilmiah\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ilkom Jurnal Ilmiah\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33096/ilkom.v14i1.1113.63-73\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ilkom Jurnal Ilmiah","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33096/ilkom.v14i1.1113.63-73","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Implementation of Artificial Neural Network (ANN) on Offline Cursive Handwriting Image Recognition
Data produced Segmentation was done using and contours. The modeling was carried out using and hard. The recognition model used the The results of the study are to be to Abstract Identifying a writing is an easy thing to do for human, but this does not apply to computers, in particular if it is handwriting. Handwriting recognition, especially cursive handwriting is a research in the area of image processing and pattern matching that is challenging to complete, following the different characteristics of each person's cursive handwriting style. In this study, the use of the ANN model will be implemented in performing offline handwriting image recognition. The cursive handwriting image that has been obtained is then preprocessed and segmented using bounding box rectangle and contour techniques. Evaluation of system performance using global performance metrics in this study resulted in a percentage of 93% where the