Robust Watermarking through Dual Band IWT and Chinese Remainder Theorem

CRT was a widely used algorithm in the development of watermarking methods. The algorithm produced good image quality but it had low robustness against compression and filtering. This paper proposed a new watermarking scheme through dual band IWT to improve the robustness and preserving the image quality. The high frequency sub band was used to index the embedding location on the low frequency sub band. In robustness test, the CRT method resulted average NC value of 0.7129, 0.4846, and 0.6768 while the proposed method had higher NC value of 0.7902, 0.7473, and 0.8163 in corresponding Gaussian filter, JPEG, and JPEG2000 compression test. Meanwhile the both CRT and proposed method had similar average SSIM value of 0.9979 and 0.9960 respectively in term of image quality. The result showed that the proposed method was able to improve the robustness and maintaining the image quality

ROBUST INTEGER HAAR WAVELET BASED WATERMARKING USING SINGULAR VALUE DECOMPOSITION

This paper proposed a hybrid watermarking method that used dither quantization of Singular Value Decomposition (SVD) on average coefficients of Integer Haar Wavelet Transform (IHWT). The watermark image embeds through dither quantization process on singular coefficients value. This scheme aims to obtain the higher robustness level than previous method which performs dither quantization of SVD directly on image pixels value. The experiment results show that the proposed method has proper watermarked images quality above 38dB. The proposed method has better performance than the previous method in term of robustness against several image processing attacks. In JPEG compression with Quality Factor of 50 and 70, JPEG2000 compression with Compression Ratio of 5 and 3, average filtering, and Gaussian filtering, the previous method has average Normalized Correlation (NC) values of 0.8756, 0.9759, 0.9509, 0.9905, 0.8321, and 0.9297 respectively. While, the proposed method has better average NC values of 0.9730, 0.9884, 0.9844, 0.9963, 0.9020, and 0.9590 respectively

Robust image watermarking scheme by discrete wavelet transform

This paper proposes a robust digital image watermarking techniques by using discrete wavelet transform. The watermark is embedded in 2-level diagonal coefficient to achieve high performance in term of imperceptibility. The watermark is embedded by selecting a seed that generating pseudorandom noise sequence. Then the Watermark is extracted back by using the same pseudorandom noise sequence seed in the embedding. The experimental results show that the proposed algorithm provides good level of imperceptibility. Moreover, the watermarked image is robust against several attacks

Symmetry-Adapted Machine Learning for Information Security

Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis

Implementación de un modelo computacional basado en inteligencia artificial para la representación del Boterismo en objetos y seres vivos

Trabajo de investigaciónEl objetivo de este proyecto fue crear una herramienta a través de inteligencia artificial el cual es capaz de recrear el estilo artístico propio del pintor Colombiano Fernando Botero con el fin de que su estilo perdure por generaciones haciendo que sus obras de arte sirvan de inspiraciones a las nuevas generaciones de pintores.1. INTRODUCCIÓN 2. JUSTIFICACIÓN 3. PLANTEAMIENTO DEL PROBLEMA 4. OBJETIVOS 5. ALCANCES Y LIMITACIONES 6. MARCO DE REFERENCIA 7. METODOLOGÍA 8. ESTADO DEL ARTE 9. RECOPILACIÓN DE INFORMACIÓN 10. IMPLEMENTACIÓN DEL ALGORITMO 11. REALIZAR PRUEBAS DEL ALGORITMO Y SU FUNCIONAMIENTO 12. CONCLUSIONES 13. TRABAJOS FUTUROS 14. BIBLIOGRAFÍAPregradoIngeniero de Sistema