 Subjects -> ELECTRONICS (Total: 207 journals)
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- Application Research and Improvement of Weighted Information Fusion
Algorithm and Kalman Filtering Fusion Algorithm in Multi-sensor Data
Fusion Technology-
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Abstract: Abstract In order to improve the accuracy and reliability of the collected data, the weighted information fusion algorithm and the Kalman filtering fusion algorithm in multi-sensor data fusion technology are researched and improved. Firstly, the definition of multi-sensor data fusion and the basic working principle of multi-sensor data fusion are expounded. Structural models of multi-sensor data fusion are introduced, the existing problems of multi-sensor data fusion are analyzed, the development trend of data fusion is pointed out. Secondly, the multi-sensor data fusion algorithms are analyzed, the weighted information fusion fusion algorithm and Kalman filtering algorithm in multi-sensor data fusion technology are focused on. Aiming at the deficiency of the weighted information fusion algorithm, an information fusion algorithm combining the jackknife method and the adaptive weighted method is proposed, and the basic steps of the improved fusion algorithm are given. The algorithm makes full use of the observed values and the estimated values of each historical moment, Quenouille estimation on the estimated values is performed by constructing pseudo-values. On the basis of the traditional Kalman filtering algorithm, an improved filtering algorithm is proposed, and a new state estimation equation is derived, which both treats the field value to prevent the filtering divergence, and introduces the observed value at the next moment to the state estimate at the current moment. Finally, improved fusion algorithms are applied and simulated in intelligent monitoring systems. Application and simulation results show that improved fusion algorithms are effective and superior, they have high reliability and anti-interference performances, the accuracy of the data is greatly increased, and they play a positive role in promoting the wide application of multi-sensor data fusion technology.
PubDate: 2023-11-16
- A Tantalum Disulfide (TaS2) Mediated Long-Range Surface Plasmon Resonance
Refractive Index Sensor with Improved Performance-
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Abstract: Abstract In this manuscript, we comprehensively evaluate a newly devised biosensor that utilizes the Kretschman configuration and incorporates Tantalum Disulfide (TaS2) for Long Range Surface Plasmon Resonance (LRSPR). We optimized the performance of the sensor by simulating with different metals [specifically, gold (Au), silver (Ag), and aluminium (Al)] and four distinct dielectric buffer layers (namely, LiF, Teflon, Cytop, and MgF2) using MATLAB software. The most favourable configuration emerges when we employ a 28 nm thick Al layer and 800 nm thick MgF2 layer. It yields exceptional performance parameters, particularly in response to variations in the refractive index (RI) of the sensing medium (SM, nSM = 1.33–1.38). These parameters include a reduced full width at half maximum (FWHM) of 0.1 Deg., enhanced detection accuracy (DA) at 10 (1/Deg.), imaging figure of merit (IFOM) measuring 26,903 [(Deg. RIU)]−1, an angular figure of merit (FOMang.) of 189.9 (RIU−1), and an imaging sensitivity (Simg.) of 2690.3 RIU−1 at a wavelength of 633 nm. Comparing the LRSPR sensor to the conventional SPR (CSPR) sensor, it significantly outperforms them with 7.053 times higher Simg., 57.84 times higher IFOM, 8.20 times higher DA, and 4.61 times higher FOMang. The analysis performed using COMSOL Multiphysics software demonstrates that the proposed LRSPR biosensor achieves a notably deeper penetration depth (PD) of 348.25 nm, surpassing the PD of CSPR sensors (PD = 197.65 nm). This remarkable PD underlines the potential of the proposed sensor for highly precise and sensitive RI sensing, placing it as a promising contender for diverse biomedical applications.
PubDate: 2023-11-11
- Long Range and Wide Field of View Thermal Detection Miniature System with
a Conical Horn-
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Abstract: Abstract We demonstrate a novel approach, to the best of our knowledge, to collect and detect thermal infrared signals from relatively hot objects with a focusing conical horn and non-matrix (single element) thermal sensor. The presented technique includes a horn as an alternative to a lens which allows to vary human detection range and field of view. Through theoretical research, we obtained the gain characteristics of the conical horn depending on its design parameters and observation angle when a single reflection on the horn’s inner conical surface is considered. To detect humans at long distances (up to 40 m), the use of narrow horns with cone apex angles of 16° ÷ 30° is recommended, while horns with apex angles of 45° ÷ 60° provide considerable detection range and field of view. The developed technique can be applied in indoor and outdoor environments for safety purposes to monitor humans, vehicles and prevent fires.
PubDate: 2023-11-02
- Visible and Infrared Image Fusion Using Distributed Anisotropic Guided
Filter-
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Abstract: Abstract The fusion of infrared (IR) and visible (VI) images should result in a more informative image, which can then be used for human inspection or other computer vision applications. In this article, VI and IR images are fused based on the proposed Distributed Anisotropic Guided Filter (DAGF). With the intent of fixing some widespread problems like smoothing, averaging, edge preservation, and sustaining the spectral content of conventional methods. To acquire low-pass and high-pass information, VI and IR images are transformed into detail layer (DL) and base layer (BL) layers through the multiscale decomposition property of DAGF. Next, a fused BL will be generated through a weighted average of the saliency map (SM) and BL. Fused DL will be produced through maximum absolute grades of DLs and spatially varying weights. This optimization tries to transmit more visual information into the fused image while transferring a lesser amount of unnecessary IR information and noise. Finally, the algebraic sum of fused detail and fused base layers will generate the desired VI and IR fused image. This would make the details of the fused image look more natural and in line with human visual perception. Several tests, quantitative and qualitative, have revealed that the proposed technique excels at a subset of the state-of-the-art alternatives.
PubDate: 2023-11-01
- Ultrasound and X-ray Cross-Characterization of a Graded Impedance Impactor
used for Shock-Ramp Compression Experiments-
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Abstract: Abstract In this work we perform ultrasound measurements on an impedance graded impactor made by tape casting magnesium, copper, and tungsten. We also destructively extract small representative samples from the part for complementary characterization with x-ray computed tomography. Combining the two data sets enables direct assignment of some of the measured ultrasound features to specific material characteristics identified by x-ray tomography. Our results demonstrate how ultrasound inspection, informed by x-ray computed tomography, can be used to identify sub-millimeter material amalgamations and spatial heterogeneities in this graded material.
PubDate: 2023-10-30
- Artificial Neural Network Based Sub-surface Defect Detection in Glass
Fiber Reinforced Polymers: Nondestructive Evaluation 4.0-
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Abstract: Abstract With the rapid development of Industry 4.0 and the expansion of its application fields, it has been successfully applied in various industrial applications like aerospace, defense, material manufacturing, etc. For quality control, nondestructive testing and evaluation (NDT&E) will become nondestructive testing and evaluation (NDE) 4.0 to seamlessly connect with Industry 4.0. NDE 4.0 focuses on deploying artificial intelligence in the quality inspection of different industrial products, including composites, steel slabs, polycrystalline solar wafers, etc. This paper proposes an artificial neural network (ANN) based sub-surface defect detection modality for exploring subsurface defects using Gabor filter features with improved resolution and enhanced detectability. Considering the desirable characteristics of spatial locality and orientation selectivities of the Gabor filter, we design filters for extracting sample features from the local image. The effectiveness of the proposed method is demonstrated by the experimental results on glass fiber reinforced polymer (GFRP) composite sample using digitized frequency modulated thermal wave imaging. We experimentally evaluate the proposed model on a benchmark and achieve a fast detection result with high accuracy, surpassing the state-of-the-art methods. For quantification, signal to noise ratio (SNR) is considered as a figure of merit.
PubDate: 2023-10-27
- Rhodamine-Based Fluorescent Nanogel: A Dual Temperature and pH Sensor
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Abstract: Abstract We have prepared a pH and thermosensitive, fluorescent nanogel based on sodium alginate and itaconic acid as pH-sensitive moieties, diethylene glycol methyl ether acrylate as thermosensitive monomer and rhodamine B monomer as pH-sensitive fluorescent dye. The nanogel was characterized by Fourier transform infrared spectroscopy (FT-IR) and proton nuclear magnetic resonance (1HNMR) spectroscopy. Also, scanning electron microscope (SEM) images were taken and indicated the relative uniform spherical particles with average diameter 250–300 nm. By enhancing the fluorescence emission at 576 nm, we confirmed that the pH sensitive property of the nanogel was more effective than that of the bare rhodamin B. Moreover, the nanogel including the diethylene glycol methyl ether acrylate exhibited changes in fluorescence intensity induced by temperature. By heating the nanogel dispersion to 40 °C, at acidic pH the rhodamine emission showed a considerable increase. This result indicated the occurrence of an efficient fluorescence resonance energy transfer (FRET) process between fluorescence dye and polymeric nanogel in collapsed state. Also, the thermo-responsibility of the nanogel was studied by dynamic light scattering (DLS) analysis which indicated the change in hydrodynamic diameter by changing the temperature.
PubDate: 2023-10-25
- Enhancement of an RSSI-Based Min–Max Localization Method with Forbidden
Zone Consideration for Indoor Corridor Environments-
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Abstract: Abstract In this paper, a received signal strength indicator-based localization system for target tracking in indoor corridor environments is proposed. The major contributions of this work are two-fold. First, a min–max method with forbidden zone consideration (i.e., the dangerous area or the empty area in corridor environments) is proposed to improve the accuracy of the target localization and tracking in a building corridor. When the estimated position falls into the forbidden zone, the estimated position adjustment will be performed by sliding to the nearest zone as the appropriate zone. Second, experiments that verify the efficiency of the proposed method compared with the traditional min–max method are provided. Experiments in the indoor corridor environment using a 2.4 GHz, IEEE 802.15.4 ZigBee wireless sensor network with four reference nodes in the test field dimension of 22 m × 9.3 m have been performed. Results reveal that, for fixed eight target nodes placed in the test field, the traditional min–max has an average localization error of 1.85 m with a standard deviation (SD) of 0.728 (i.e., a min. error of 0.532 m and a max. error of 4.020 m), where five estimated target positions are outside the corridors and fall into the forbidden zone. Whereas the error by the proposed method is 0.885 m with a SD of 0.375 (i.e., a min. error of 0.305 m and a max. error of 1.774 m). Here, the proposed method outperforms the min–max method by 52.189%, and all estimated positions are in the corridor areas of 100%. Moreover, the experiments also show that, for mobile target tracking, the proposed method can efficiently locate and track the moving target within the corridor, while the estimated positions by the traditional min–max method frequently stray outside or fall into the forbidden zone. Finally, the computational cost analysis of the proposed method and the min–max method in terms of mathematical operations is discussed in this paper. Both the best case and worst case scenarios and the computational cost obtained from the experimental data are also reported.
PubDate: 2023-09-30
- Microfluidic Detection of Water Contamination Using THz Antenna with
Metamaterials: Analysis of Silver Nanospheres in the THz Spectrum-
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Abstract: Abstract THz antenna with wide bandwidth and high Q-factor is interesting for various applications including 6G applications and THz sensing and controlling the surface current of the antenna is known as a technique for bandwidth enhancement. The slot antenna with metasurface is a good candidate for this aim. In this research, we have suggested a multilayer slot antenna with metamaterial load to provide wide bandwidth which covers the 1.08 to 1.8 THz with more than 50%, and the Q-factor is increased up to 213. The metamaterial loads make various paths for the current on the surface of the antenna that makes it possible to achieve a wider bandwidth. The proposed antenna has a gain of 7.74 dBi. This antenna is considered part of a system for THz sensing and for this aim, it is combined with a microfluidic structure which is pinpointed over the surface of the antenna. Pure water with various percentages of nanoparticles of Ag (Silver) is considered as material under test (MUT). The sensitivity and figure of merit for the antenna for the MUTs are obtained to recognize the percentage of Ag nanoparticles in the water. The proposed antenna is simulated with the full wave time domain technique of FIT (finite integrated technique).
PubDate: 2023-09-21
- Detection of Viruses by Molecularly Imprinted Polymer Based Smart Sensors:
The Current Scenario-
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Abstract: Abstract The current scenario of crisis for virus threatening all over the world demands the development of a virus detection system that would be accurate, rapid, easy to operate, cost effective, and should involve less manpower. Many such detection kits are already in place and a few of them are based on the principle of molecular imprinting. In this article, a detailed review concerning the detection of different types of viruses using the principle of molecularly imprinted polymer (MIP) based technique is presented. The present treatise details the principle of detection based on MIP and subsequently outlines the advantages of this technique. Further, the implementation of the MIP technique for the development of sensing materials in order to detect different types of viruses pursued by the researchers has been described.  
PubDate: 2023-09-21
- A Novel Hybrid Optimization Enabled Densenet for Covid-19 Classification
using CT Images-
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Abstract: Abstract Corona Virus disease 2019 (Covid-19) is an acute disease that affects the respiratory system alveolar of the human, which leads to serious illness and may cause death. When an infected person coughs, sneezes, speaks, sings, or breathes, the virus can spread from their mouth or nose in minute liquid particles. Disease diagnosis using Computed Tomography (CT) images is widely utilized to detect infection; still, accurate detection is a challenging task. Hence, this research introduces a novel hybrid optimization enabled DenseNet for Covid-19 classification. The hybrid optimization, named Gradient Mutated Leader Algorithm (GMLA) is proposed for tuning the weights of DenseNet by combining the Mutated leader's behavior in guiding the group member in position updation with the gradient descent algorithm for the acquisition of computation efficiency with stable convergence, which helps to obtain the global best solution for tuning the DenseNet's weights to make the classification more accurate. In addition, the proposed GMLA_DenseNet utilizes the data augmentation technique using rotating, shifting, zooming, and flipping to obtain balanced data with enormous data sizes, which makes the classification more efficient. The performance of GMLA_DenseNet is evaluated using True Negative Rate (TNR), True Positive Rate (TPR), Precision, and segmentation accuracy and obtained the maximal values of 0.920, 0.919, 0.919, and 0.919, respectively.
PubDate: 2023-09-19
DOI: 10.1007/s11220-023-00434-5
- Radio Frequency Based Sensor for Adulteration Measurement in a Continuous
Two Phase-Flow of Alcoholic Beverages-
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Abstract: Abstract The adulteration in alcoholic beverage has costed thousands of lives and malnutrition’s specifically in developing countries. The existing characterization methods such as Gas Chromatography (GC) and Bioassay and Spectroscopy (NMR) offer insights into the chemical composition but the techniques are costlier and bulkier, hence the testing is evitable in a limited number of cases. This paper discloses the novel radio frequency (RF) technology based sensors and integrated into a device to detect the presence of ethanol in beverages. The proposed sensor is two phase flow sensor as the liquid can continuously move while being sensed by the sensor. The conducting patch of the RF sensing antenna is zig–zag shaped sensor. The sensor sends the signals at RF frequencies to the liquid. The RF signal gets scattered from liquid and receive back by transceiver with a specific time and phase delay. The proposed zig–zag sensor is portable as it is smaller in size (radiating structure has dimensions of \(12 \mathrm{mm} \times 40 \mathrm{mm}\) ). The substrates have a running polysiloxane microfluidic channel where the samples of alcoholic beverages are applied. The device operates at frequencies of 4.592 GHz and 6.458 GHz. The ethanol concentration is detected with the help of a radio frequency spectroscopy. The results are validated with characterization with nuclear magnetic resonance (NMR).
PubDate: 2023-09-19
DOI: 10.1007/s11220-023-00441-6
- Refractive Index Sensing Using Tamm Plasmons in Photonic Quasicrystals
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Abstract: Abstract In this paper, we have conducted a thorough investigation into the characteristics, behavior and formation of Optical plasmon Tamm states in an aperiodic metal distributed Bragg reflector geometry and also theoretically demonstrated the refractive index sensor based on the specific geometry. We focused on a particular structure known as a one-dimensional photonic quasi-crystal, where the layers are arranged in a Fibonacci sequence. The reflection and transmission characteristics of electromagnetic wave through the multilayer geometry are studied and investigated using transfer matrix method. Additionally, we performed a comparative analysis between periodic and aperiodic structures, assessing their sensitivity, detection accuracy, quality factor, and figure of merit for a refractive index sensor operating within the visible wavelength range. We could achieve a maximum sensitivity of 221 nm/RIU for which the periodic structure yielded a figure of merit of 26.89 RIU−1, quality factor of 71.3 and a detection accuracy of 0.12 nm−1. For the aperiodic structure we achieved a maximum sensitivity of 213 nm/RIU with figure of merit value of 24.32 RIU−1, quality factor of 82.8 and detection accuracy value equal to 0.11 nm−1. These values can further be tuned by varying the geometrical parameters of the structures along with different spacer layer thickness. The present study will be extremely useful for active and passive optoelectronic miniature devices in future.
PubDate: 2023-09-19
DOI: 10.1007/s11220-023-00435-4
- A Novel Ultrasound Elastography Configuration for Simultaneous Measurement
of Contact Forces-
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Abstract: Abstract The current state of clinical strain ultrasound elastography scanning is marked by the absence of a quantifiable, consistent, and reproducible method for measuring the contact pressure applied by the ultrasound transducer during the scanning process. This gap presents a significant challenge as it restricts the ability to control the factors that might influence imaging outcomes, such as operator variations. On the other hand, quantitative transducer contact pressure measurements implemented in ultrasound strain elastography imaging is a promising solution to reduce the impact of operator variations on imaging outcomes and produce instantaneous quantitative estimations of Young’s modulus. Using miniature pressure sensors with the required accuracy would enable contact pressure measurement in ultrasound strain elastography. An inhomogeneous phantom with multiple layers, each with different mechanical properties, showed an elevated stress magnitude with a decreasing pattern closer to the irregular boundary. Additionally, the surface contact pressure and internal stress distribution studies on phantoms showed good agreement with our finite element method models, with error values of less than 10%. This shows that during breast deformation, the pressure sensor arrays are able to detect initial contact and measure contact pressure. In accordance with the findings and estimated errors from simulation studies and obtained pressure values from pressure sensors, our approach can depict the stress distribution and facilitates assessing the contract pressure during ultrasound strain elastography imaging.
PubDate: 2023-09-17
DOI: 10.1007/s11220-023-00438-1
- Nickel-Doped Cadmium Sulphide as a Promising Nanomaterials for Humidity
Sensing Applications-
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Abstract: Abstract Humidity sensors are utilized in respiratory analysis, noncontact sensing, electronic skin, and other exciting fields of study in current era. This study is focused on the synthesis of nickel (Ni)-doped cadmium sulfide (CdS) using hydrothermal method. The synthesized nanomaterials were characterized by Powder X-ray diffraction (PXRD), Fourier-transform infrared (FTIR) spectroscopy, Energy-dispersive X-ray spectroscopy (EDX) and Field emission scanning electron microscopy (FESEM). The PXRD analysis confirmed the formation of pure and crystalline nanomaterials. FESEM imaging revealed the morphology of the synthesized nanomaterials. The EDX confirmed the elemental composition and revealed the efficiency of adopted synthesis method. FTIR spectroscopy provided insight into the chemical bonding and functional groups present in the nickel-doped CdS nanomaterials. Furthermore, the synthesized Ni-doped CdS nanomaterials were first time explored as thin-film humidity sensors, and their humidity-sensing performance was evaluated. The developed humidity sensor has a response time of 12.36 s and a recovery time of 16.38 s, good repeatability, and a negligible ageing effect. A comparison of current investigations with earlier reports reveals that in terms of recovery, response time and material the designed sensor is promising.
PubDate: 2023-09-16
DOI: 10.1007/s11220-023-00440-7
- A Dielectric Modulated Step-Channel Junction-Less TFET (DM-SC-JLTFET) for
Label-Free Detection of Breast Cancer Cells: Design and Sensitivity
Analysis-
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Abstract: Abstract This work designs a novel dielectric modulated step channel Junctionless tunnel field effect (DM-SC-JLTFET) for the label-free detection of breast cancer cells using their dielectric constant (K) values. The dielectric modulation technique is exploited to detect breast cancer cells (BCC) whose K values are observed at 200 MHz frequency using an open-ended coaxial probe technique. The charge plasma concept is employed to suppress the random dopant fluctuation (RDF). The usage of this concept rendering the complex fabrication process simple and affordable. A novel step channel structure has been implemented with reduced substrate thickness for the TFET device that improves the efficacy of the biosensor. The proposed device uses on-current (Ion) and ambipolar current (Iamb) to measure the sensitivity of cancer biomolecules. An in-depth analysis has been carried out for the biosensor by considering performance parameters such as the electrostatics of the device, energy band diagram, lateral electric field, and threshold voltage (Vth). The device sensitivity is analyzed using parameters like Ion/Ioff, Ioff/Iamb current ratio, Subthreshold Swing (SS), and Vth. The proposed device reports high detection sensitivity of 2.683 × 106 and a low SS of 32 mV/dec for breast cancer cell biomolecule T47D (K = 32), effectively reducing the RDF effect. The simulated device shows enhanced sensitivity and higher compatibility for breast cancer cell detection, and this device will be an excellent alternative to classical vivo breast cancer detection.
PubDate: 2023-09-14
DOI: 10.1007/s11220-023-00439-0
- High Performance Biosensor for Detection of the Normal and Cancerous Liver
Tissues Based on 1D Photonic Band Gap Material Structures-
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Abstract: Abstract In the present research work, we have theoretically examined the biosensing capabilities of microcavity-based one-dimensional photonic crystal suitable for identifying the primary and secondary-stage cancerous and non-cancerous liver tissues. To carry out investigations we have used MATLAB computational tool in addition to the transfer matrix method. The propagation of an electromagnetic wave through the proposed biosensing structure loaded with the sample under investigation has been studied under both normal and oblique incidence cases corresponding to transverse electric waves only. The present work highlights the effect of change in cavity layer thickness, period number, and angle of incidence on the performance of the proposed design. This study helps us to explore optimum conditions under which the structure works as a sensitive biosensor. The idea of this work may be useful for designing of various microcavity based 1D photonic crystal-based biosensors capable of investigating various fluids of the human body for the prevention of the spreading of cancerous and other liver related diseases.
PubDate: 2023-08-28
DOI: 10.1007/s11220-023-00432-7
- Micromirror Arrays as Optical Phase Modulators for Free-Space Beam
Steering-
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Abstract: Abstract Generally, a group of sub-micron or nanometer sized optical phase shifters or modulators are used in an optical phased array (OPA) based scanner so as to selectively perturb wavefronts of outgoing laser beams. Similar to the concept of light propagation through a prism, an array of phase shifters is responsible for linearly delaying or advancing the propagating light waves. Optical phased array (OPA) systems have become an emerging technology for many applications due to the compact designs that eliminate the need for robust physical moving parts, leading to their fast response, high reliability, and low power requirements. Micromirror based OPA systems are fundamentally different than the conventional micromirror arrays that were being developed for numerous applications such as spectroscopy, digital light processing projectors, laser communication, and confocal microscopy. Those micromirror arrays provide significantly different motion types, actuation strokes, and operating speeds, due to the distinct task requirements by their target applications. Most of the previously designed conventional micromirror arrays are not suitable for high-speed laser beam steering at wide field of view due to either the large mirror sizes or the large array pitch sizes. MEMS based OPA systems generally demand narrow and tightly spaced suspended microstructures with high-aspect-ratio in lateral dimensions, rendering some significant challenges in the system design, fabrication, and integration. In addition, the scanners are required to generate hundreds to thousands of scan points along a far-field scan line which results in a large number of phase shifters in the arrays and high complexity in control.
PubDate: 2023-08-28
DOI: 10.1007/s11220-023-00433-6
- An Efficient Image Forgery and Region Detection Using LogDIoU-Faster RCNN
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Abstract: Abstract In different scientific and security or surveillance applications, the identification of content-altering manipulation from a video or an image has emerged as a field of increasing interest. Enormous traditional methodologies have been developed over time for detecting image forgeries. Nevertheless, most image forgery methodologies, which exist in the literature are constrained to detecting a specific sort of forgery (either image splicing or else copy-move). Thus, a scheme capable of efficiently as well as accurately detecting the availability of unseen forgeries in an image is essential. A Logit Normalization and Distance Intersection over Union-centered fast regional convolutional neural network (LogDIoU-Faster RCNN) technique is created by the work aimed at IF along with region detection. Concurrently, the region localization and also forgery detection process is executed. Utilizing Dual Band Pass Filter Based Steerable Pyramid Transform (DBPF-SPT), the image is initially decomposed by the framework into numerous sub-bands. For recognizing the forgery along the disparate scales, frequencies, along with orientations, decomposition is used. After that, utilizing Normalized Extended Local Ternary Pattern-Principal Component Analysis (NELTP-PCA), the essential key points are extracted together with chosen from the sub-bands that preserve the image’s informative features and also reduce computational complexity. The image is finally identified by LogDIoU- Faster RCNN as a forgery image or not, and also the forgery’s location is localized. Superior detection accuracy concerning both categorizing the forgery and also identifying the region is attained by the framework. It stays robust when analogized to the existent top-notch methods as exhibited by the experimental outcomes.
PubDate: 2023-08-17
DOI: 10.1007/s11220-023-00429-2
- Modeling Automated Image Watermarking Using Meta-heuristic-based Deep
Learning with Wavelet Approach-
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Abstract: Abstract Accessing digital media has become quite a simple result of the fast rise of multimedia in the case of network technology. As a result, safeguarding intellectual property necessitates a greater focus on image watermarking. Distinct image watermarking systems have been introduced for this purpose; however, they have limitations with transparency and robustness. In the sphere of digital watermarking, multimedia copyright protection plays a critical part. The practice of extracting and embedding a watermark discreetly on a carrier image is called digital image watermarking. Digital watermarking is successful in securing digital data; it also has sparked a lot of study attention nowadays. Deep learning networks combined with wavelet-oriented approaches for image watermarking have gotten a lot of interest these days. Conventional watermarking techniques, on the other hand, cannot provide blindness, resilience, and automated extraction and embedding all at the same time. In this circumstance, this paper motivates to offer an improved approach for generating watermarked images with elevated invisibility using deep learning with a novel wavelet-based technique. Initially, after gathering the data, image griding is performed to partition the images into grids, thus making the image suitable for efficient feature extraction. Then, the two techniques named Deep feature extraction by Convolutional Neural Network and Neighboring-based features are extracted. Using these features, the Modified Deep Neural Network (MDNN) is used for choosing the regions for embedding the watermark. Here, the training algorithm of DNN is optimized by the Squirrel Search Algorithm (SSA) and Grey Wolf Optimization (GWO), known as Squirrel Search–Grey Wolf Optimization (SS–GWO). Once the regions are selected, watermark embedding is performed by the Adaptive Discrete Wavelet Transform (ADWT) with filter coefficient optimization by the same SS–GWO based on a newly derived fitness function. Accordingly, the message extraction is achieved using the same ADWT with the embedding key. Throughout the results, the mean of SS–GWO-MDNN + ADWT is 31.25%, 10.53%, 16.67%, and 23.53% improved than SSA-MDNN + ADWT, GWO-MDNN + ADWT, PSO-MDNN + ADWT, and JA-MDNN + ADWT regarding Gaussian filtering attack for dataset 3. The simulation findings, and a comparison of prior approaches, suggest that the developed mode has a considerable increase in image processing attack robustness, making it ideal for copyright protection applications.
PubDate: 2023-07-12
DOI: 10.1007/s11220-023-00427-4
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Hybrid journal (It can contain Open Access articles)
