{"title":"基于阈值二值化的BP神经网络边缘检测","authors":"H. Mehrara, Mohammad Zahedinejad, A. Pourmohammad","doi":"10.1109/ICCEE.2009.144","DOIUrl":null,"url":null,"abstract":"One of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the Edge of image where the preciseness and reliability of its results will affect directly the comprehension machine system made for objective world. Several edge detectors have been developed in the past decades, although no single edge detectors have been developed satisfactorily enough for all application. In this paper, a new edge detection technique is proposed basis on the BP neural network. Here, it is classified the edge patterns of binary images into 16 possible types of visual patterns. In the following, After training the pre-defined edge patterns, the BP neural network is applied to correspond any type of edges with its related visual pattern. The results demonstrated that the new proposed technique provides the better results compared with traditional edge detection techniques while improved the computations complexity.","PeriodicalId":343870,"journal":{"name":"2009 Second International Conference on Computer and Electrical Engineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":"{\"title\":\"Novel Edge Detection Using BP Neural Network Based on Threshold Binarization\",\"authors\":\"H. Mehrara, Mohammad Zahedinejad, A. Pourmohammad\",\"doi\":\"10.1109/ICCEE.2009.144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the Edge of image where the preciseness and reliability of its results will affect directly the comprehension machine system made for objective world. Several edge detectors have been developed in the past decades, although no single edge detectors have been developed satisfactorily enough for all application. In this paper, a new edge detection technique is proposed basis on the BP neural network. Here, it is classified the edge patterns of binary images into 16 possible types of visual patterns. In the following, After training the pre-defined edge patterns, the BP neural network is applied to correspond any type of edges with its related visual pattern. The results demonstrated that the new proposed technique provides the better results compared with traditional edge detection techniques while improved the computations complexity.\",\"PeriodicalId\":343870,\"journal\":{\"name\":\"2009 Second International Conference on Computer and Electrical Engineering\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"38\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Second International Conference on Computer and Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEE.2009.144\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Second International Conference on Computer and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEE.2009.144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Novel Edge Detection Using BP Neural Network Based on Threshold Binarization
One of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the Edge of image where the preciseness and reliability of its results will affect directly the comprehension machine system made for objective world. Several edge detectors have been developed in the past decades, although no single edge detectors have been developed satisfactorily enough for all application. In this paper, a new edge detection technique is proposed basis on the BP neural network. Here, it is classified the edge patterns of binary images into 16 possible types of visual patterns. In the following, After training the pre-defined edge patterns, the BP neural network is applied to correspond any type of edges with its related visual pattern. The results demonstrated that the new proposed technique provides the better results compared with traditional edge detection techniques while improved the computations complexity.