scholarly journals Digital Watermarking using Grasshopper Optimization Algorithm

2021 ◽  
Vol 11 (1) ◽  
pp. 330-336
Author(s):  
Satender Sharma ◽  
Usha Chauhan ◽  
Ruqaiya Khanam ◽  
Krishna Kant Singh
Keyword(s):  
Digital Watermarking ◽  
Optimization Algorithm ◽  
Signal To Noise Ratio ◽  
Scaling Factor ◽  
The Other ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Inverse Dct

Abstract The advancement in computer science technology has led to some serious concerns about the piracy and copyright of digital content. Digital watermarking technique is widely used for copyright protection and other similar applications. In this paper, a technique for digital watermarking based on Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Grasshopper Optimization Algorithm (GOA) is proposed. The method computes the DWT of the cover image to obtain the sub-components of the image. The subcomponent is converted to frequency domain using DCT. The challenge is to find the optimal scaling factor to be used for watermarking. The authors have designed a GOA based technique that finds the optimized scaling factor and the coefficient for embedding the watermark. GOA makes the watermark undetectable and is invisible in the cover image. The watermark image is embedded in the cover image using these coefficients. The extraction of watermark from the cover image is done by using inverse DCT and DWT. The proposed method is compared with the other state of the art methods. The effectiveness of the proposed method is computed using Peak Signal to Noise Ratio (PSNR), Normalized Cross Correlation (NCC) and Image Fidelity (IF). The proposed method outperforms the other methods and can be effectively used for practical digital watermarking.

An Efficient Digital Watermarking Technique for Color Images Using Directional Transforms

2017 ◽  
Vol 3 (2) ◽  
pp. 1
Author(s):  
Nguyen Chi Sy ◽  
Ha Hoang Kha ◽  
Nguyen Minh Hoang
Keyword(s):  
Wavelet Transform ◽  
Digital Watermarking ◽  
Performance Metrics ◽  
Signal To Noise Ratio ◽  
Structural Similarity ◽  
Color Images ◽  
The Other ◽  
Discrete Wavelet ◽  
Signal To Noise ◽  
Transform Domains

This paper is concerned with a digital watermarking technique for color images based on directional transforms. Different from the traditional watermarking schemes which embed the watermarks into the spatial domain or frequency domain of the Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT), this paper investigates the performance of the watermarking schemes using the Fast Discrete Curvelet Transforms (FDCT) and Contourlet Transform (CT). We evaluate the performance of the watermarking schemes using the directional transforms on a standard database of color images in terms of invisibility and robustness. The performance metrics are measured by Peak Signal-to-Noise Ratio (PSNR), Normalized Correlation (NC), Structural SIMilarity (SSIM) and required time for extracting and embedding process. The experimental results reveal that watermarking schemes in the directional transform domains outperform the other schemes in DWT domains.

Evaluvation of Multiresolution Watermarking Algorithm

2017 ◽  
Vol 7 (8) ◽  
pp. 85
Author(s):  
S. Thabasu Kannan ◽  
S. Azhagu Senthil
Keyword(s):  
Digital Watermarking ◽  
Wavelet Transformation ◽  
Signal To Noise Ratio ◽  
Rapid Development ◽  
Threshold Value ◽  
Discrete Wavelet ◽  
Digital Production ◽  
Common Framework ◽  
Sampling Operation ◽  
Watermarking Scheme

Now-a-days watermarking plays a pivotal role in most of the industries for providing security to their own as well as hired or leased data. This paper its main aim is to study the multiresolution watermarking algorithms and also choosing the effective and efficient one for improving the resistance in data compression. Computational savings from such a multiresolution watermarking framework is obvious. The multiresolutional property makes our watermarking scheme robust to image/video down sampling operation by a power of two in either space or time. There is no common framework for multiresolutional digital watermarking of both images and video. A multiresolution watermarking based on the wavelet transformation is selected in each frequency band of the Discrete Wavelet Transform (DWT) domain and therefore it can resist the destruction of image processing.   The rapid development of Internet introduces a new set of challenging problems regarding security. One of the most significant problems is to prevent unauthorized copying of digital production from distribution. Digital watermarking has provided a powerful way to claim intellectual protection. We proposed an idea for enhancing the robustness of extracted watermarks. Watermark can be treated as a transmitted signal, while the destruction from attackers is regarded as a noisy distortion in channel.  For the implementation, we have used minimum nine coordinate positions. The watermarking algorithms to be taken for this study are Corvi algorithm and Wang algorithm. In all graph, we have plotted X axis as peak signal to noise ratio (PSNR) and y axis as Correlation with original watermark. The threshold value ά is set to 5. The result is smaller than the threshold value then it is feasible, otherwise it is not.

Robust design of a robot gripper mechanism using new hybrid grasshopper optimization algorithm

2021 ◽  
Author(s):  
Betül Sultan Yildiz ◽  
Nantiwat Pholdee ◽  
Sujin Bureerat ◽  
Ali Riza Yildiz ◽  
Sadiq M. Sait
Keyword(s):  
Robust Design ◽  
Optimization Algorithm ◽  
Robot Gripper ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization

An Image Segmentation Method Based on Two-Dimensional Entropy and Chaotic Lightning Attachment Procedure Optimization Algorithm

2020 ◽  
Vol 34 (11) ◽  
pp. 2054030 ◽  
Author(s):  
Wei Liu ◽  
Shuai Yang ◽  
Zhiwei Ye ◽  
Qian Huang ◽  
Yongkun Huang
Keyword(s):  
Image Segmentation ◽  
Maximum Entropy ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Computational Time ◽  
Two Dimensional ◽  
Threshold Segmentation ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Competitive Algorithms

Threshold segmentation has been widely used in recent years due to its simplicity and efficiency. The method of segmenting images by the two-dimensional maximum entropy is a species of the useful technique of threshold segmentation. However, the efficiency and stability of this technique are still not ideal and the traditional search algorithm cannot meet the needs of engineering problems. To mitigate the above problem, swarm intelligent optimization algorithms have been employed in this field for searching the optimal threshold vector. An effective technique of lightning attachment procedure optimization (LAPO) algorithm based on a two-dimensional maximum entropy criterion is offered in this paper, and besides, a chaotic strategy is embedded into LAPO to develop a new algorithm named CLAPO. In order to confirm the benefits of the method proposed in this paper, the other seven kinds of competitive algorithms, such as Ant–lion Optimizer (ALO) and Grasshopper Optimization Algorithm (GOA), are compared. Experiments are conducted on four different kinds of images and the simulation results are presented in several indexes (such as computational time, maximum fitness, average fitness, variance of fitness and other indexes) at different threshold levels for each test image. By scrutinizing the results of the experiment, the superiority of the introduced method is demonstrated, which can meet the needs of image segmentation excellently.

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