A ECG steganography provides safe communication over internet such as transformation of patient information embed on ECG signals. The data hiding technique are used here in which steganography is hiding the patient information in image, video, audio and signal etc. The very important challenge to ECG steganography is extract data and signal without loss. İn this technique, we use the curvelet transform for evaluating coefficients, converts information into binary format by using quantization and adaptive LSB algorithm for embedding. The ECG signals for steganography are taken from database of MIT-BIH. From outcome we have observed that the signal loss is less after embedding when the coefficients near to zero. The overlapping of embed watermark is avoided by using sequence. The performance is observed by using parameter such as peak signal to noise ratio, percentage residual difference, correlation and time elapsed at embedding. The extraction performance is measured by using correlation, BER and time elapsed parameters. At extraction bit error rate is used to calculate extract capacity. The size of patient information is raises then BER is zero but the original signal deteroiates. Curvelet transform removes the limitation of wavelet transform and watermarking technique. Hence the curvelet transform is very efficient technique.
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CITATION STYLE
Patil, V., & Patil, M. (2018). Curvelet based ECG steganography for protection of data. In Lecture Notes in Computational Vision and Biomechanics (Vol. 28, pp. 238–248). Springer Netherlands. https://doi.org/10.1007/978-3-319-71767-8_20