{"title":"基于Contourlet变换的多字体阿拉伯字符特征提取方法","authors":"N. Amor, N. Amara","doi":"10.1109/ICDAR.2007.45","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a method for features extraction from multifont Arabic characters images based on the Contourlet Transform, which has been recently introduced. In our previous works, we noticed that Wavelet transforms are not capable of reconstructing curved images perfectly; the Contourlet Transform offers a solution to remedy to this insufficiency. It allows a multiresolution and directional decomposition of a signal using a combination of Laplacian Pyramid (LP) and a Directional Filter Bank (DFB). The Contourlet Transform has good approximation properties for smooth 2D functions and finds a direct discrete-space construction, and is therefore computationally efficient. Experimental tests have been carried out on a set of 175.000 samples of characters corresponding to 9 different Arabic fonts. Some promising experimental results are reported.","PeriodicalId":294655,"journal":{"name":"IEEE International Conference on Document Analysis and Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"An Approach for Multifont Arabic Characters Features Extraction Based on Contourlet Transform\",\"authors\":\"N. Amor, N. Amara\",\"doi\":\"10.1109/ICDAR.2007.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a method for features extraction from multifont Arabic characters images based on the Contourlet Transform, which has been recently introduced. In our previous works, we noticed that Wavelet transforms are not capable of reconstructing curved images perfectly; the Contourlet Transform offers a solution to remedy to this insufficiency. It allows a multiresolution and directional decomposition of a signal using a combination of Laplacian Pyramid (LP) and a Directional Filter Bank (DFB). The Contourlet Transform has good approximation properties for smooth 2D functions and finds a direct discrete-space construction, and is therefore computationally efficient. Experimental tests have been carried out on a set of 175.000 samples of characters corresponding to 9 different Arabic fonts. Some promising experimental results are reported.\",\"PeriodicalId\":294655,\"journal\":{\"name\":\"IEEE International Conference on Document Analysis and Recognition\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Document Analysis and Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.2007.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.2007.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Approach for Multifont Arabic Characters Features Extraction Based on Contourlet Transform
In this paper, we propose a method for features extraction from multifont Arabic characters images based on the Contourlet Transform, which has been recently introduced. In our previous works, we noticed that Wavelet transforms are not capable of reconstructing curved images perfectly; the Contourlet Transform offers a solution to remedy to this insufficiency. It allows a multiresolution and directional decomposition of a signal using a combination of Laplacian Pyramid (LP) and a Directional Filter Bank (DFB). The Contourlet Transform has good approximation properties for smooth 2D functions and finds a direct discrete-space construction, and is therefore computationally efficient. Experimental tests have been carried out on a set of 175.000 samples of characters corresponding to 9 different Arabic fonts. Some promising experimental results are reported.