Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.

A semantic segmentation-based underwater acoustic image transmission framework for cooperative SLAM

With the development of underwater sonar detection technology,simultaneous localization and mapping(SLAM)approach has attracted much attention in underwater navigation field in recent years.But the weak detection ability of a single vehicle limits the SLAM performance in wide areas.Thereby,cooperative SLAM using multiple vehicles has become an important research direction.The key factor of cooperative SLAM is timely and efficient sonar image transmission among underwater vehicles.However,the limited bandwidth of underwater acoustic channels contradicts a large amount of sonar image data.It is essential to compress the images before transmission.Recently,deep neural networks have great value in image compression by virtue of the powerful learning ability of neural networks,but the existing sonar image compression methods based on neural network usually focus on the pixel-level information without the semantic-level information.In this paper,we propose a novel underwater acoustic transmission scheme called UAT-SSIC that includes semantic segmentation-based sonar image compression(SSIC)framework and the joint source-channel codec,to improve the accuracy of the semantic information of the reconstructed sonar image at the receiver.The SSIC framework consists of Auto-Encoder structure-based sonar image compression network,which is measured by a semantic segmentation network's residual.Considering that sonar images have the characteristics of blurred target edges,the semantic segmentation network used a special dilated convolution neural network(DiCNN)to enhance segmentation accuracy by expanding the range of receptive fields.The joint source-channel codec with unequal error protection is proposed that adjusts the power level of the transmitted data,which deal with sonar image transmission error caused by the serious underwater acoustic channel.Experiment results demonstrate that our method preserves more semantic information,with advantages over existing methods at the same compression ratio.It also improves the error tolerance and packet loss resistance of transmission.

A Hybrid Cybersecurity Algorithm for Digital Image Transmission over Advanced Communication Channel Models

The efficient transmission of images,which plays a large role inwireless communication systems,poses a significant challenge in the growth of multimedia technology.High-quality images require well-tuned communication standards.The Single Carrier Frequency Division Multiple Access(SC-FDMA)is adopted for broadband wireless communications,because of its low sensitivity to carrier frequency offsets and low Peak-to-Average Power Ratio(PAPR).Data transmission through open-channel networks requires much concentration on security,reliability,and integrity.The data need a space away fromunauthorized access,modification,or deletion.These requirements are to be fulfilled by digital image watermarking and encryption.This paper ismainly concerned with secure image communication over the wireless SC-FDMA systemas an adopted communication standard.It introduces a robust image communication framework over SC-FDMA that comprises digital image watermarking and encryption to improve image security,while maintaining a high-quality reconstruction of images at the receiver side.The proposed framework allows image watermarking based on the Discrete Cosine Transform(DCT)merged with the Singular Value Decomposition(SVD)in the so-called DCT-SVD watermarking.In addition,image encryption is implemented based on chaos and DNA encoding.The encrypted watermarked images are then transmitted through the wireless SC-FDMA system.The linearMinimumMean Square Error(MMSE)equalizer is investigated in this paper to mitigate the effect of channel fading and noise on the transmitted images.Two subcarrier mapping schemes,namely localized and interleaved schemes,are compared in this paper.The study depends on different channelmodels,namely PedestrianAandVehicularA,with a modulation technique namedQuadratureAmplitude Modulation(QAM).Extensive simulation experiments are conducted and introduced in this paper for efficient transmission of encrypted watermarked images.In addition,different variants of SC-FDMA based on the Discrete Wavelet Transform(DWT),Discrete Cosine Transform(DCT),and Fast Fourier Transform(FFT)are considered and compared for the image communication task.The simulation results and comparison demonstrate clearly that DWT-SC-FDMAis better suited to the transmission of the digital images in the case of PedestrianAchannels,while the DCT-SC-FDMA is better suited to the transmission of the digital images in the case of Vehicular A channels.

A Method of Coding and Decoding in Underwater Image Transmission

A new method of coding and decoding in the system of underwater image transmission is introduced, including the rapid digital frequency synthesizer in multiple frequency shift keying, image data generator, image grayscale decoder with intelligent fuzzy algorithm, image restoration and display on microcomputer.

Irregular and regular LDPC codes with high spectrum efficiency modulation in image transmission over fading channel

If the degree distribution is chosen carefully, the irregular low-density parity-check (LDPC) codes can outperform the regular ones. An image transmission system is proposed by combining regular and irregular LDPC codes with 16QAM/64QAM modulation to improve both efficiency and reliability. Simulaton results show that LDPC codes are good coding schemes over fading channel in image communication with lower system complexity. More over, irregular codes can obtain a code gain of about 0.7 dB compared with regular ones when BER is 10 -4. So the irregular LDPC codes are more suitable for image transmission than the regular codes.

Reconstruction and transmission of astronomical image based on compressed sensing

In the process of image transmission, the famous JPEG and JPEG-2000 compression methods need more transmission time as it is difficult for them to compress the image with a low compression rate. Recently the compressed sensing（CS） theory was proposed, which has earned great concern as it can compress an image with a low compression rate, meanwhile the original image can be perfectly reconstructed from only a few compressed data. The CS theory is used to transmit the high resolution astronomical image and build the simulation environment where there is communication between the satellite and the Earth. Number experimental results show that the CS theory can effectively reduce the image transmission and reconstruction time. Even with a very low compression rate, it still can recover a higher quality astronomical image than JPEG and JPEG-2000 compression methods.

Principle and realization method of tunnel deformation detection based on image recognition and data transmission technology

基于图象传感器网络检测隧道结构的变丑是空间传感器技术的先进学习和应用程序。为内部、外部的应力在它的长时期操作以后引起的 metro 隧道的垂直解决，全面计划和隧道变丑察觉系统的测量原则被介绍。图象数据获得并且察觉目标处理被图象传感器的合作工作完成，手臂嵌入的系统。RS485 通讯完成在手臂存储器和主机计算机之间的数据传播。在车站站台的数据库系统分析察觉数据并且获得变丑状态掘内部墙，它使它可能到早警告隧道变丑并且及时采取预防措施。

Gradient based restoration of coal mine images obtained by underground wireless transmissions

Curvature-driven diffusion (CDD) principles were used to develop a novel gradient based image restora- tion algorithm. The algorithm fills in blocks of missing data in a wireless image after transmission through the network. When images are transmitted over fading channels, especially in the severe circum- stances of a coal mine, blocks of the image may be destroyed by the effects of noise. Instead of using com- mon retransmission query protocols the lost data is reconstructed by using the adaptive curvature-driven diffusion (ACDD) image restoration algorithm in the gradient domain of the destroyed image. Missing blocks are restored by the method in two steps: In step one, the missing blocks are filled in the gradient domain by the ACDD algorithm; in step two, and the image is reconstructed from the reformed gradients by solving a Poisson equation. The proposed method eliminates the staircase effect and accelerates the convergence rate. This is demonstrated by experimental results.

Adaptive optimization on ultrasonic transmission tomography-based temperature image for biomedical treatment

Hyperthermia has proven to be beneficial to treating superficial malignancies, particularly chest wall recurrences of breast cancer. During hyperthermia, monitoring the time–temperature profiles in the target and surrounding areas is of great significance for the effect of therapy. An ultrasound-based temperature imaging method has advantages over other approaches. When the temperature around the tumor is calculated by using the propagation speed of ultrasound, there always exist overshoot artifacts along the boundary between different tissues. In this paper, we present a new method combined with empirical mode decomposition（EDM）, similarity constraint, and continuity constraint to optimize the temperature images. Simulation and phantom experiment results compared with those from our previously proposed method prove that the EMD-based method can build a better temperature field image, which can adaptively yield better temperature images with less computation for assistant medical treatment control.

Joint Detection for Image Transmission Based on Schur Algorithm over Wireless Sensor Network

To achieve much efficient multimedia transmission over an error-prone wireless network, there are still some problem must to be solved, especially in energy limited wireless sensor network. In this paper, we propose a joint detection based on Schur Algorithm for image wireless transmission over wireless sensor network. To eliminate error transmissions and save transmission energy, we combine Schur algorithm with joint dynamic detection for wireless transmission of JPEG 2000 encoded image which we proposed in [1]. Schur algorithm is used to computing the decomposition of system matrix to decrease the computational complexity. We de-scribe our transmission protocol, and report on its performance evaluation using a simulation testbed we have designed for this purpose. Our results clearly indicate that our method could approach efficient images transmission in wireless sensor network and the transmission errors are significantly reduced when compared to regular transmissions.

EFFICIENT IMAGE TRANSMISSION SCHEME IN FMT SYSTEM

An efficient image transmission scheme is proposed based on byte partition and adaptive sub-channel distribution technique in Filtered MultiTone (FMT) system over frequency selective slow fading channel. According to the simulation results and analysis of a typical image with matlab, improvement in Peak Signal to Noise Ratio (PSNR) of the received image and low complexity for equalization is demonstrated remarkably. Comparing with no adaptive and no actual channel equalization scheme, the proposed scheme saves over 6 dB when PSNR=40 dB.

Information loss recovery for JPEG2000 image transmission in an error-prone environment

Information loss recovery techniques are important for transmitting images over error-prone channels at the decoder. A novel error recovery scheme for JPEG2000 image is presented in this paper, which adopts different techniques for the lowest frequency coefficients and high frequency coefficients in the wavelet domain. The low-frequency recovery algorithm was implemented by adopting the watermarking technique and the packet structure of JPEG2000. The low-frequency coefficients taken as the hidden data were extracted from the compressed bit stream, and then were embedded back into the bit stream itself prior to transmission. The embedded data were used to recover the information loss. High-frequency reconstruction was performed in bitplane base. The damaged bitplanes were recovered according to the correlation in the wavelet subband structure and by using the algorithm based on the horizontal and vertical edge detection. Experiments verified the effectiveness of these algorithms.

Underwater Acoustic Image Transmission System Based on DSF

The underwater acoustic image transmission system based on the high-speed DSP device TMS320C549 has been studied.We use Goertzel algorithm for source decoding and MFSK for modulation.Turbo code is used for channel coding and decoding.The purpose is to implement underwater video image data transmission.

DESIGN OF MODULATION AND COMPRESSION CODING IN UNDERWATER ACOUSTIC IMAGE TRANSMISSION

This paper describes the design of modulation, compression coding and transmission control in underwater acoustic color image transmission system. This design adapts a special system of modulation and transmission control based on a DSP(Digital Signal Processing) chip, to cope with the complex underwater acoustic channel. The hardware block diagram and software flow chart are presented.

DESIGN OF IRREGULAR LDPC CODE WITH UNEQUAL ERROR PROTECTION PROPERTY AND ITS PERFORMANCE ANALYSIS ON IMAGE TRANSMISSION

Based on the property that high degree variable nodes within an irregular LowDensity Parity-Check (LDPC) code have more powerful error-correcting capability than that of low degree variable nodes, a group of irregular LDPC codes with Unequal Error Protection (UEP)property is designed in this letter. Simulation results show that the transmission quality of the image may be effectively improved with this class of irregular LDPC code.

Transmissive multifocal laser speckle contrast imaging through thick tissue

Laser speckle contrast imaging(LSCI)is a powerful tool for monitoring blood flow changes in tissue or vessels in vivo,but its applications are limited by shallow penetration depth under reflective imaging configuration.The traditional LSCI setup has been used in transmissive imaging for depth extension up to 2l_(t)–3l_(t)(l_(t)is the transport mean free path),but the blood flow estimation is biased due to the depth uncertainty in large depth of field(DOF)images.In this study,we propose a transmissive multifocal LSCI for depth-resolved blood flow in thick tissue,further extending the transmissive LSCI for tissue thickness up to 12lt.The limited-DOF imaging system is applied to the multifocal acquisition,and the depth of the vessel is estimated using a robust visibility parameter V_(r)in the coherent domain.The accuracy and linearity of depth estimation are tested by Monte Carlo simulations.Based on the proposed method,the model of contrast analysis resolving the depth information is established and verified in a phantom experiment.We demonstrated its effectiveness in acquiring depth-resolved vessel structures and flow dynamics in in vivo imaging of chick embryos.

Automated deep learning system for power line inspection image analysis and processing: architecture and design issues

The continuous growth in the scale of unmanned aerial vehicle (UAV) applications in transmission line inspection has resulted in a corresponding increase in the demand for UAV inspection image processing. Owing to its excellent performance in computer vision, deep learning has been applied to UAV inspection image processing tasks such as power line identification and insulator defect detection. Despite their excellent performance, electric power UAV inspection image processing models based on deep learning face several problems such as a small application scope, the need for constant retraining and optimization, and high R&D monetary and time costs due to the black-box and scene data-driven characteristics of deep learning. In this study, an automated deep learning system for electric power UAV inspection image analysis and processing is proposed as a solution to the aforementioned problems. This system design is based on the three critical design principles of generalizability, extensibility, and automation. Pre-trained models, fine-tuning (downstream task adaptation), and automated machine learning, which are closely related to these design principles, are reviewed. In addition, an automated deep learning system architecture for electric power UAV inspection image analysis and processing is presented. A prototype system was constructed and experiments were conducted on the two electric power UAV inspection image analysis and processing tasks of insulator self-detonation and bird nest recognition. The models constructed using the prototype system achieved 91.36% and 86.13% mAP for insulator self-detonation and bird nest recognition, respectively. This demonstrates that the system design concept is reasonable and the system architecture feasible .

SNR-adaptive deep joint source-channel coding scheme for image semantic transmission with convolutional block attention module

With the development of deep learning(DL),joint source-channel coding(JSCC)solutions for end-to-end transmission have gained a lot of attention.Adaptive deep JSCC schemes support dynamically adjusting the rate according to different channel conditions during transmission,enhancing robustness in dynamic wireless environment.However,most of the existing adaptive JSCC schemes only consider different channel conditions,ignoring the different feature importance in the image processing and transmission.The uniform compression of different features in the image may result in the compromise of critical image details,particularly in low signal-to-noise ratio(SNR)scenarios.To address the above issues,in this paper,a dual attention mechanism is introduced and an SNR-adaptive deep JSCC mechanism with a convolutional block attention module(CBAM)is proposed,in which matrix operations are applied to features in spatial and channel dimensions respectively.The proposed solution concatenates the pooling feature with the SNR level and passes it sequentially through the channel attention network and spatial attention network to obtain the importance evaluation result.Experiments show that the proposed solution outperforms other baseline schemes in terms of peak SNR(PSNR)and structural similarity(SSIM),particularly in low SNR scenarios or when dealing with complex image content.

Design of interference-imaging spectrum data transmission Card Based on PCI Bus

Take the interference- imaging spectrometer for exam-ple, the paper analyses the characters of the spectrum- formingsignals and their timing sequence. Then inspects the key tech-nology in the interference - imaging spectrum data transmissionsystem, and indicates a design for the system- - which is basedon computer PCI bus with CPLD technique imbedded. The sys-tem’ s circuitry and function are also presented.