C. Shekhar, S. Kuttikkad, R. Chellappa, M. Thonnat
{"title":"Knowledge-based integration of IU algorithms","authors":"C. Shekhar, S. Kuttikkad, R. Chellappa, M. Thonnat","doi":"10.1109/ICPR.1996.547635","DOIUrl":null,"url":null,"abstract":"This paper deals with the integration of image understanding (IU) programs using a knowledge-based approach. The basic concepts of program integration are discussed, and a simple problem-solving model for program integration is outlined. Two types of reasoning, planning and execution control, are identified. A system developed using this model, called OCAPI (Optimizing, Controlling and Automating the Processing of Images), is introduced. OCAPI is an AI environment in which the reasoning used by the IU specialist is formally represented using frames and production rules. An example of the application developed using OCAPI is presented, and the advantages and shortcomings of this approach are discussed.","PeriodicalId":290297,"journal":{"name":"Proceedings of 13th International Conference on Pattern Recognition","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 13th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.1996.547635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper deals with the integration of image understanding (IU) programs using a knowledge-based approach. The basic concepts of program integration are discussed, and a simple problem-solving model for program integration is outlined. Two types of reasoning, planning and execution control, are identified. A system developed using this model, called OCAPI (Optimizing, Controlling and Automating the Processing of Images), is introduced. OCAPI is an AI environment in which the reasoning used by the IU specialist is formally represented using frames and production rules. An example of the application developed using OCAPI is presented, and the advantages and shortcomings of this approach are discussed.