{"title":"Compressive Sensing and Histogram Adaptive Fuzzy Image Steganography","authors":"Yoga Adhy Nugraha, Irma Safitri, Ratri Dwi Atmaja","doi":"10.1109/ISRITI.2018.8864460","DOIUrl":null,"url":null,"abstract":"We proposed compressive sensing (CS) and histogram adaptive fuzzy (HAF) for the image steganography system. Based on our experiments, red layer is the best color layer for insertion with the acquisition of the average PSNR value of 36.15912 dB. While the best subband is in the high high or HH subband with an average PSNR value of 42,65717 dB. Meanwhile, the stego image has the highest PSNR value of 63,9643 dB. Our system can have BER = 0 and PSNR = 30.5574 dB by using the Barcode.bmp file as the message image. We have BER = 0.0122 with a measurement rate of 30%.","PeriodicalId":162781,"journal":{"name":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISRITI.2018.8864460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We proposed compressive sensing (CS) and histogram adaptive fuzzy (HAF) for the image steganography system. Based on our experiments, red layer is the best color layer for insertion with the acquisition of the average PSNR value of 36.15912 dB. While the best subband is in the high high or HH subband with an average PSNR value of 42,65717 dB. Meanwhile, the stego image has the highest PSNR value of 63,9643 dB. Our system can have BER = 0 and PSNR = 30.5574 dB by using the Barcode.bmp file as the message image. We have BER = 0.0122 with a measurement rate of 30%.