{"title":"基于相似性度量和反向传播神经网络的图像定位算法","authors":"Jun Yan, Hongliu Zhu","doi":"10.1109/ICEICT51264.2020.9334204","DOIUrl":null,"url":null,"abstract":"In this paper, an image based localization technique is proposed by similarity measurements and back-propagation neural network (BPNN). First, the bilinear interpolation method is used for size normalization of the obtained images. Then, the relative distance is calculated as the label of each collection position. The image similarity measurements, such as cosine, Hist and SSIM similarity are chosen as the fingerprint of the collection position. At last, the BPNN is utilized for regression learning and obtain the distance based regression function. Field tests show that the proposed algorithm can obtain more accurate position estimation than other existing image based localization approaches.","PeriodicalId":124337,"journal":{"name":"2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image Based Localization Algorithm Using Similarity Measurements and Back-Propagation Neural Network\",\"authors\":\"Jun Yan, Hongliu Zhu\",\"doi\":\"10.1109/ICEICT51264.2020.9334204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an image based localization technique is proposed by similarity measurements and back-propagation neural network (BPNN). First, the bilinear interpolation method is used for size normalization of the obtained images. Then, the relative distance is calculated as the label of each collection position. The image similarity measurements, such as cosine, Hist and SSIM similarity are chosen as the fingerprint of the collection position. At last, the BPNN is utilized for regression learning and obtain the distance based regression function. Field tests show that the proposed algorithm can obtain more accurate position estimation than other existing image based localization approaches.\",\"PeriodicalId\":124337,\"journal\":{\"name\":\"2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT)\",\"volume\":\"115 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEICT51264.2020.9334204\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEICT51264.2020.9334204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image Based Localization Algorithm Using Similarity Measurements and Back-Propagation Neural Network
In this paper, an image based localization technique is proposed by similarity measurements and back-propagation neural network (BPNN). First, the bilinear interpolation method is used for size normalization of the obtained images. Then, the relative distance is calculated as the label of each collection position. The image similarity measurements, such as cosine, Hist and SSIM similarity are chosen as the fingerprint of the collection position. At last, the BPNN is utilized for regression learning and obtain the distance based regression function. Field tests show that the proposed algorithm can obtain more accurate position estimation than other existing image based localization approaches.