A robust blind color image watermarking based on Fourier transform domain

Unmanned aerial vehicles (UAVs) or Drones technology has a huge potential for supporting different efficient solutions for the smart applications in our world. The applications include sma...

A survey on recent optimal techniques for securing unmanned aerial vehicles applications

Digital image watermarking techniques have been developed widely in recent years to maintain the broadcasting media and content authentication, broadcast monitoring, copy control, and many other applications. Therefore, many studies have used digital image watermarking to solve these problem. This paper highlights digital image watermarking. It starts with a basic model of digital image watermarking, it discusses the main requirements and applications. Moreover, it reviews some of the techniques and algorithm used in image watermarking. In addition, digital image watermarking attacks are discussed. Lastly, Watermarking evaluation system is described.

Properties of digital image watermarking

In order to contribute to the security of medical image, we present in this paper a blind and robust watermarking technique that allows the integration of the electronic patient’s record into a computerized tomography scan. In this approach, a discrete wavelet transform is applied to the image before the integration process, then, a topological reorganization of the coefficients of the LL sub-bands is done by the ZigZag scanning method. The obtained coefficients are then combined to integrate the watermark bits. A hash of the electronic patient record being integrated in the image, the integrity of the watermark can easily be verified. After the evaluation of our approach in terms of invisibility and robustness, the experimental results obtained show that our approach offers excellent imperceptibility (with a PSNR above 70 dB) and very good robustness against several geometric and destructive attacks.

A DWT based watermarking approach for medical image protection

A DWT-SVD based robust digital watermarking for medical image security

Digital watermarking is a technique which allows an individual to add hidden copyright notices or other verification messages to digital audio, video, or image signals and documents. Watermarking can be done by using least significant bit (LSB), singular value decomposition (SVD), Discrete Fourier Transform (DFT), Discrete cosine transform (DCT) and Discrete wavelet transform (DWT) techniques. In this paper Discrete cosine transform (DCT) and Discrete wavelet transform (DWT) are used for embedding and extraction of watermark. DWT and DCT are compared with respect to peak signal to noise ratio (PSNR) at a different threshold values. DWT gives better Image quality then DCT.

Digital Image Watermarking by Using Discrete Wavelet Transform and Discrete Cosine Transform and Comparison Based on PSNR

Globally, fresh vegetables are a crucial part of our lives and they provide most of the vitamins, minerals, and proteins, in short, every nutrition that a growing body need. They vary in colors like; red, green, and yellow but as our ancestors say that green vegetables are a must for every age. To identify the fresh vegetable that makes our body healthy and notion positive the proposed automatic multi-class vegetable classifier is used. In this paper, a framework based on a deep learning approach has been proposed for multi-class vegetable classification from scratch. The accuracy of the proposed model is further increased using the transfer-learning concept (DenseNet201). The whole process is divided into four modules; data collection and pre-processing, data splitting, CNN model training, and testing, and performance improvement using a pre-trained DenseNet201 network. Data augmentation and data shuffling are used to free from lack of data availability during the training phase of the model. The proposed framework is more efficient and can predict the type of vegetables comparatively in less computational time (2 to 3 minutes) with an ‘Accuracy’ of 98.58%, ‘Sensitivity’ of 98.23%, and ‘Specificity’ of 94.25%.

Automatic Framework for Vegetable Classification using Transfer-Learning

False-positive problem (FPP) is a one of the challenging tasks for the researchers. It authenticates the wrong owner to access the multimedia content. To overcome, the FPP problem, this paper introduces an efficient watermarking method based on the selection of highest entropy blocks. In this method, cover and watermark images are initially shuffled through Arnold transform. Then, the encrypted images are further processed by a 2-level discrete wavelet transform followed by singular value decomposition. The proposed method has been evaluated with geometrical, filtering, noise, and contrast adjustment attacks on the standard image datasets against five recently developed watermarking methods. The simulation results reveal that the proposed method outperforms the existing methods.

https://ieeexplore.ieee.org/ielx7/6287639/6514899/09774329.pdf

Efficient Watermarking Method Based on Maximum Entropy Blocks Selection in Frequency Domain for Color Images

From classical to soft computing based watermarking techniques: A comprehensive review

The researchers have a difficult task in preserving the trade-off between robustness and imperceptibility. To address this problem, this paper presents a discrete cosine transform (DCT)-singular value decomposition (SVD)-based watermarking technique. This technique initially partitioned the host image into 8 × 8 DC blocks followed by DCT. The encrypted watermark logo by the Arnold transform is concealed into the SVD blocks of host image. The performance of the presented technique is measured against Lena and Barbara images under ten watermarking attacks in terms of PSNR and NC. The simulation results validate that the proposed techniques performs well than the compared watermarking schemes.

Roop Singh

Papers

Digital Image Watermarking by Using Discrete Wavelet Transform and Discrete Cosine Transform and Comparison Based on PSNR

Automatic Framework for Vegetable Classification using Transfer-Learning

Efficient Watermarking Method Based on Maximum Entropy Blocks Selection in Frequency Domain for Color Images

From classical to soft computing based watermarking techniques: A comprehensive review

DS-AT: An efficient watermarking technique based on Arnold transform in DCT and SVD domain