Assessment of the complexity of input data preprocessing procedures for implementing steganographic transformations
Year: 2025
Type: article
Abstract: An assessment of the complexity of input data preprocessing procedures has been carried out, which ensures the necessary preparation and processing of data for the implementation of content (image) encapsulation procedures within the modeling of the first stage of a hybrid steganographic algorithm. The results obtained confirm that optimized smoothing of low-information areas significantly improves computational efficiency and information hiding quality. Balanced parameter settings allow to achieve a balance between image quality, container capacity, and resistance to unauthorized detection. The adaptive approach ensures the scalability of the method for different types of images and its efficiency on devices with limited resources. The results obtained emphasize the importance of the correct selection of parameters to optimize computations and increase the reliability of steganographic transformations.
Source: InterConf
Authors: Mykyta Honcharov, Serhii Malakhov
Institution: V. N. Karazin Kharkiv National University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7084581199