{"title":"使用上下文相关标准的徽标识别","authors":"Poonam Kondekar, P. Shende","doi":"10.1109/ICAECCT.2016.7942565","DOIUrl":null,"url":null,"abstract":"In our day today life if we want to buy any product then we first see the brand or logo of that product whether that brand or logo is original or not. Depending upon this we conclude that product is original product otherwise fake product. So in this project we detect first the original logo which is present in the image by comparing original logo image with the test image by using two algorithms first CDS-SIFT and second CDS RANSAC. And then conclude that the proposed method is more efficient than the existing method in terms of Execution time, Accuracy, FRR(False Rejection Rate), FAR (False Acceptance Rate). The proposed method of logo detection is based on Context Dependent Similarity (CDS) kernel. CDS kernel's function is dependent upon three terms first energy function, second context criterion and third entropy term. Energy function balances the fidelity term. The analysis of proposed method is done using MATLAB and comparative analysis of proposed method against the nearest neighbor of existing SIFT method is done and claim that proposed method is best method. Secondly we will evaluate the performance parameters.","PeriodicalId":6629,"journal":{"name":"2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)","volume":"140 1","pages":"111-115"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Logo recognition using Context Dependent criteria\",\"authors\":\"Poonam Kondekar, P. Shende\",\"doi\":\"10.1109/ICAECCT.2016.7942565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In our day today life if we want to buy any product then we first see the brand or logo of that product whether that brand or logo is original or not. Depending upon this we conclude that product is original product otherwise fake product. So in this project we detect first the original logo which is present in the image by comparing original logo image with the test image by using two algorithms first CDS-SIFT and second CDS RANSAC. And then conclude that the proposed method is more efficient than the existing method in terms of Execution time, Accuracy, FRR(False Rejection Rate), FAR (False Acceptance Rate). The proposed method of logo detection is based on Context Dependent Similarity (CDS) kernel. CDS kernel's function is dependent upon three terms first energy function, second context criterion and third entropy term. Energy function balances the fidelity term. The analysis of proposed method is done using MATLAB and comparative analysis of proposed method against the nearest neighbor of existing SIFT method is done and claim that proposed method is best method. Secondly we will evaluate the performance parameters.\",\"PeriodicalId\":6629,\"journal\":{\"name\":\"2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)\",\"volume\":\"140 1\",\"pages\":\"111-115\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAECCT.2016.7942565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAECCT.2016.7942565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In our day today life if we want to buy any product then we first see the brand or logo of that product whether that brand or logo is original or not. Depending upon this we conclude that product is original product otherwise fake product. So in this project we detect first the original logo which is present in the image by comparing original logo image with the test image by using two algorithms first CDS-SIFT and second CDS RANSAC. And then conclude that the proposed method is more efficient than the existing method in terms of Execution time, Accuracy, FRR(False Rejection Rate), FAR (False Acceptance Rate). The proposed method of logo detection is based on Context Dependent Similarity (CDS) kernel. CDS kernel's function is dependent upon three terms first energy function, second context criterion and third entropy term. Energy function balances the fidelity term. The analysis of proposed method is done using MATLAB and comparative analysis of proposed method against the nearest neighbor of existing SIFT method is done and claim that proposed method is best method. Secondly we will evaluate the performance parameters.