Selection of the Best Color Space for Image Steganography with the Least Significant Bit Method

Darmawan, Irfan and Nurdian, Iman and Rahmatulloh, Alam and Rianto, Rianto Selection of the Best Color Space for Image Steganography with the Least Significant Bit Method. In: 2022 International Conference Advancement in Data Science, E-learning and Information Systems (ICADEIS).

	Text 11. Selection of the Best Color Space for Image Steganography with the Least Significant Bit Method.pdf Download (1MB)
	Text 2.B2-Korespondensi Selection of the.pdf Download (35kB)
	Text 2.B2-Similaritas Selection of the.pdf Download (2MB)
	Text 11. Sertifikat Selection of the.pdf Download (2MB)

Abstract

Various kinds of security techniques have been developed to protect and maintain data confidentiality in order to avoid security problems, one of which is steganography techniques. Steganography techniques are used so that message protection or hiding secret messages does not raise suspicion for the attacker. The most commonly used steganographic embedding method is the least significant bit with image media. Current technological developments and advances make many different color spaces. However, it is not yet known the best color space for steganographic images in digital images. In this study, the performance and image quality of the eight best color spaces were compared, namely RGB, HSV, HSI, XYZ, LAB, YIQ, YUV, and YCbCr. The images used as experiments in this study are pictures of lena and baboons. The comparison results obtained with the evaluation criteria of image quality with eight measurement methods, namely NAE, NCC, MSE, PSNR, AD, MD, SC, and SSIM. Resulting that the image in the Hue Saturation Value (HSV) color space has better performance than other color spaces. This can be seen from the results of the test which got the best six values out of eight parameters for the flax image, namely HSV 1.36E-05, NCC 0.999997, MSE 0.0190582, PNSR 65.364, AD 0.0019302, and SC 1. While the baboon image got the five best values, namely MSE 0.0607897, PNSR 60.3265, MD 181, SC 1, and SSIM 0.999992

Item Type:	Conference or Workshop Item (Paper)
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Informatika > Artikel Dosen Informatika
Depositing User:	Mrs Linda Amelia Oktavia
Date Deposited:	15 May 2023 04:01
Last Modified:	19 May 2023 08:35
URI:	http://repositori.unsil.ac.id/id/eprint/9186

Actions (login required)

View Item