{"title":"Intelligent FPGA based system for shape recognition","authors":"E. C. Pedrino, O. Morandin, E. Kato, V. O. Roda","doi":"10.1109/SPL.2011.5782648","DOIUrl":null,"url":null,"abstract":"Mathematical morphology supplies powerful tools for low level image analysis, with applications in many areas. In this paper, the development of a novel reconfigurable hardware using a genetic algorithm and a pipeline architecture is proposed for the task of shape recognition in binary images. For the recognition process, a large sized convex structuring element representing the object shape to be recognized is decomposed into the architecture stages. Each stage can handle structuring elements of a limited size. In this approach, a genetic algorithm was used to decompose this structuring element. Thus, a simple erosion performed in each stage is used to detect the goal object. The hardware is capable of processing binary images at high speed. The developed system is based on FPGAs. Our approach represents an intelligent mechanism to reconfigure the pipeline architecture, it is different from other systems found in the literature, and the obtained results are promising.","PeriodicalId":6329,"journal":{"name":"2011 VII Southern Conference on Programmable Logic (SPL)","volume":"8 1","pages":"197-202"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 VII Southern Conference on Programmable Logic (SPL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPL.2011.5782648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
Mathematical morphology supplies powerful tools for low level image analysis, with applications in many areas. In this paper, the development of a novel reconfigurable hardware using a genetic algorithm and a pipeline architecture is proposed for the task of shape recognition in binary images. For the recognition process, a large sized convex structuring element representing the object shape to be recognized is decomposed into the architecture stages. Each stage can handle structuring elements of a limited size. In this approach, a genetic algorithm was used to decompose this structuring element. Thus, a simple erosion performed in each stage is used to detect the goal object. The hardware is capable of processing binary images at high speed. The developed system is based on FPGAs. Our approach represents an intelligent mechanism to reconfigure the pipeline architecture, it is different from other systems found in the literature, and the obtained results are promising.