Robust color image watermarking using Discrete Wavelet Transform, Discrete Cosine Transform and Cat Face Transform

The primary concern in color image watermarking is to have an effective watermarking method that can be robust against common image processing attacks such as JPEG compression, rotation, sharpening, blurring, and salt and pepper attacks for copyright protection purposes. This research examined the existing color image watermarking methods to identify their strengths and weaknesses, and then proposed a new method and the best embedding place in the host image to enhance and overcome the existing gap in the color image watermarking methods. This research proposed a new robust color image watermarking method using Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Cat Face Transform. In this method, both host and watermark images decomposed into three color channels: red, green, and blue. The second level DWT was applied to each color channel of the host image. DWT decomposed the image into four sub-band coefficients: Low-pass filter in the row, Low-pass filter in the column (LL) signifies approximation coefficient, High-pass filter in the row, Low-pass filter in the column (HL) signifies horizontal coefficient, Low-pass filter in the row, High-pass filter in the column (LH) signifies vertical coefficient, and High-pass filter in the row, High-pass filter in the column (HH) signifies diagonal coefficient. Then, HL2 and LH2 were chosen as the embedding places to improve the robustness and security, and they were divided into 4×4 non-overlapping blocks, then DCT was applied on each block. DCT turned a signal into the frequency domain, which is effective in image processing, specifically in JPEG compression due to good performance. On the other hand, the Cat Face Transform method with a private key was used to enhance the robustness of the proposed method by scrambling the watermark image before embedding. Finally, the second private key was used to embed the watermark in the host image. The results show enhanced robustness against common image processing attacks: JPEG compression (3.37%), applied 2% salt and pepper (0.4%), applied 10% salt and pepper (2%), applied 1.0 radius sharpening (0.01%), applied 1.0 radius blurring (8.1%), and can withstand rotation attack. In sum, the proposed color image watermarking method indicates better robustness against common image processing attacks compared to other reviewed methods

Combined DWT-DISB based image watermarking optimized for decision making problems

Currently, the protection of digital information, especially in the form of multimedia information such as images, video, text, and audio. The digital nature of the multimedia data has made it prone to misuse and attack, such as is of duplication, transformation, modification, and diffusion. In this sense, it is significant to create a system for protecting the intellectual property rights of the multimedia content. The system should guarantee copyright protection, authentication, and protection against duplication of the material. The drastic development in network multimedia system has made the development of these protection systems challenging. Numerous researches have proposed the use of watermarking to address these issues. The watermarking technique obscures vital information in the original multimedia data in which the hidden data is utilized for copyright protection and authentication. The primary need for any watermarking system should be to guarantee robustness against imminent attack while retaining the quality of the watermark images. This research presents a robust image watermarking technique used to hide details of the RGB Color elements. The proposed approach is an integration of the discrete wavelet transform (DWT) and the relatively new dual intermediate significant bit (DISB). The performance evaluation of the proposed approach produced quality watermarked images that are robust. The proposed method has a PSNR of 101.97 and an NCC of 0.9780 which compare considerable well with the individual techniques

Human face detection techniques: A comprehensive review and future research directions

Face detection which is an effortless task for humans are complex to perform on machines. Recent veer proliferation of computational resources are paving the way for a frantic advancement of face detection technology. Many astutely developed algorithms have been proposed to detect faces. However, there is a little heed paid in making a comprehensive survey of the available algorithms. This paper aims at providing fourfold discussions on face detection algorithms. At first, we explore a wide variety of available face detection algorithms in five steps including history, working procedure, advantages, limitations, and use in other fields alongside face detection. Secondly, we include a comparative evaluation among different algorithms in each single method. Thirdly, we provide detailed comparisons among the algorithms epitomized to have an all inclusive outlook. Lastly, we conclude this study with several promising research directions to pursue. Earlier survey papers on face detection algorithms are limited to just technical details and popularly used algorithms. In our study, however, we cover detailed technical explanations of face detection algorithms and various recent sub-branches of neural network. We present detailed comparisons among the algorithms in all-inclusive and also under sub-branches. We provide strengths and limitations of these algorithms and a novel literature survey including their use besides face detection

Fast and Efficient Foveated Video Compression Schemes for H.264/AVC Platform

Some fast and efficient foveated video compression schemes for H.264/AVC platform are presented in this dissertation. The exponential growth in networking technologies and widespread use of video content based multimedia information over internet for mass communication applications like social networking, e-commerce and education have promoted the development of video coding to a great extent. Recently, foveated imaging based image or video compression schemes are in high demand, as they not only match with the perception of human visual system (HVS), but also yield higher compression ratio. The important or salient regions are compressed with higher visual quality while the non-salient regions are compressed with higher compression ratio. From amongst the foveated video compression developments during the last few years, it is observed that saliency detection based foveated schemes are the keen areas of intense research. Keeping this in mind, we propose two multi-scale saliency detection schemes. (1) Multi-scale phase spectrum based saliency detection (FTPBSD); (2) Sign-DCT multi-scale pseudo-phase spectrum based saliency detection (SDCTPBSD). In FTPBSD scheme, a saliency map is determined using phase spectrum of a given image/video with unity magnitude spectrum. On the other hand, the proposed SDCTPBSD method uses sign information of discrete cosine transform (DCT) also known as sign-DCT (SDCT). It resembles the response of receptive field neurons of HVS. A bottom-up spatio-temporal saliency map is obtained by linear weighted sum of spatial saliency map and temporal saliency map. Based on these saliency detection techniques, foveated video compression (FVC) schemes (FVC-FTPBSD and FVC-SDCTPBSD) are developed to improve the compression performance further.Moreover, the 2D-discrete cosine transform (2D-DCT) is widely used in various video coding standards for block based transformation of spatial data. However, for directional featured blocks, 2D-DCT offers sub-optimal performance and may not able to efficiently represent video data with fewer coefficients that deteriorates compression ratio. Various directional transform schemes are proposed in literature for efficiently encoding such directional featured blocks. However, it is observed that these directional transform schemes suffer from many issues like ‘mean weighting defect’, use of a large number of DCTs and a number of scanning patterns. We propose a directional transform scheme based on direction-adaptive fixed length discrete cosine transform (DAFL-DCT) for intra-, and inter-frame to achieve higher coding efficiency in case of directional featured blocks.Furthermore, the proposed DAFL-DCT has the following two encoding modes. (1) Direction-adaptive fixed length ― high efficiency (DAFL-HE) mode for higher compression performance; (2) Direction-adaptive fixed length ― low complexity (DAFL-LC) mode for low complexity with a fair compression ratio. On the other hand, motion estimation (ME) exploits temporal correlation between video frames and yields significant improvement in compression ratio while sustaining high visual quality in video coding. Block-matching motion estimation (BMME) is the most popular approach due to its simplicity and efficiency. However, the real-world video sequences may contain slow, medium and/or fast motion activities. Further, a single search pattern does not prove efficient in finding best matched block for all motion types. In addition, it is observed that most of the BMME schemes are based on uni-modal error surface. Nevertheless, real-world video sequences may exhibit a large number of local minima available within a search window and thus possess multi-modal error surface (MES). Hence, the following two uni-modal error surface based and multi-modal error surface based motion estimation schemes are developed. (1) Direction-adaptive motion estimation (DAME) scheme; (2) Pattern-based modified particle swarm optimization motion estimation (PMPSO-ME) scheme. Subsequently, various fast and efficient foveated video compression schemes are developed with combination of these schemes to improve the video coding performance further while maintaining high visual quality to salient regions. All schemes are incorporated into the H.264/AVC video coding platform. Various experiments have been carried out on H.264/AVC joint model reference software (version JM 18.6). Computing various benchmark metrics, the proposed schemes are compared with other existing competitive schemes in terms of rate-distortion curves, Bjontegaard metrics (BD-PSNR, BD-SSIM and BD-bitrate), encoding time, number of search points and subjective evaluation to derive an overall conclusion

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering