D. Brodic, Z. Milivojevic, D. Tanikić, D. Milivojevic
{"title":"文本行分割中扩展水流算法的优化","authors":"D. Brodic, Z. Milivojevic, D. Tanikić, D. Milivojevic","doi":"10.1109/NEUREL.2012.6419975","DOIUrl":null,"url":null,"abstract":"The paper proposed an approach for the optimization of the water flow algorithm for the text-line segmentation. Original method assumed the hypothetical water that flows to the document image frame from left to right and vice versa. It used the water flow angle as the only parameter. Algorithm's extended version introduced a water flow function, which is given as the power function. It exploited two parameters: water flow angle α and exponent n. To optimize these two parameters artificial neural network has been used. Results are encouraging because of the improvement of the text-line segmentation results.","PeriodicalId":343718,"journal":{"name":"11th Symposium on Neural Network Applications in Electrical Engineering","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of the extended water flow algorithm for the text-line segmentation\",\"authors\":\"D. Brodic, Z. Milivojevic, D. Tanikić, D. Milivojevic\",\"doi\":\"10.1109/NEUREL.2012.6419975\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper proposed an approach for the optimization of the water flow algorithm for the text-line segmentation. Original method assumed the hypothetical water that flows to the document image frame from left to right and vice versa. It used the water flow angle as the only parameter. Algorithm's extended version introduced a water flow function, which is given as the power function. It exploited two parameters: water flow angle α and exponent n. To optimize these two parameters artificial neural network has been used. Results are encouraging because of the improvement of the text-line segmentation results.\",\"PeriodicalId\":343718,\"journal\":{\"name\":\"11th Symposium on Neural Network Applications in Electrical Engineering\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"11th Symposium on Neural Network Applications in Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEUREL.2012.6419975\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"11th Symposium on Neural Network Applications in Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEUREL.2012.6419975","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization of the extended water flow algorithm for the text-line segmentation
The paper proposed an approach for the optimization of the water flow algorithm for the text-line segmentation. Original method assumed the hypothetical water that flows to the document image frame from left to right and vice versa. It used the water flow angle as the only parameter. Algorithm's extended version introduced a water flow function, which is given as the power function. It exploited two parameters: water flow angle α and exponent n. To optimize these two parameters artificial neural network has been used. Results are encouraging because of the improvement of the text-line segmentation results.