Received Image Data Research Articles

A Novel Fractional Sine Chaotic Map and Its Application to Image Encryption and Watermarking

This article addresses the telecommunications industry’s priority of ensuring information security during the transition to next-generation networks. It proposes an image encryption system that combines watermarking techniques and a discrete fractional sine chaotic map. The authors also incorporate the principles of blockchain to enhance the security of transmitted and received image data. The proposed system utilizes a newly developed sine chaotic map with a fractional difference operator, exhibiting long-term chaotic dynamics. The complexity of this map is demonstrated by comparing it with three other fractional chaotic maps from existing literature, using bifurcation diagrams and the largest Lyapunov exponent. The authors also show the map’s sensitivity to changes in initial conditions through time-series diagrams. To encrypt images, the authors suggest a method involving watermarking of two secret images and encryption based on blockchain technology. The cover image is watermarked with the two hidden images using discrete wavelet transformations. Then, the image pixels undergo diffusion using a chaotic matrix generated from the discrete fractional sine chaotic map. This encryption process aims to protect the image data and make it resistant to unauthorized access. To evaluate the algorithm, the authors perform statistical analysis and critical sensitivity analysis to examine its characteristics. They also analyse different attacks to assess the algorithm’s ability to resist such threats and maintain image quality after decryption. The results demonstrate that the proposed algorithm effectively defends against attacks and ensures image security.

PocketQube development for earth exploration and vegetation monitoring

A PocketQube is being popular these days due to the enhancement in technologies for space research and earth observation. It is extremely vital to analyze the condition of vegetation on the earth surface because deforestation, forest fire and smuggling of precious plants have been increasing dramatically. The camera module in the payload captures the image from the space which helps in analyzing the vegetative condition of the forest on the earth’s surface. The provided image data is huge in order to maintain the quality of the images it captures. Hence, the received image data is further divided into chunks. Each chunks holds 64bits of hex values of each pixels of the image. The subsequent real time Image data is transmitted to the ground station and the received image is checked, analyzed and displayed on the screen. The received data is regenerated by combining the received chunks at a time at ground station. Based on the provided images further image processing activities are conducted in order to understand the condition of vegetation by calculating the vegetative index of each pixels in the received images.

A PUF-Based Data-Device Hash for Tampered Image Detection and Source Camera Identification

With the increasing prevalent of digital devices and their abuse for digital content creation, forgeries of digital images and video footage are more rampant than ever. Digital forensics is challenged into seeking advanced technologies for forgery content detection and acquisition device identification. Unfortunately, existing solutions that address image tampering problems fail to identify the device that produces the images or footage while techniques that can identify the camera is incapable of locating the tampered content of its captured images. In this paper, a new perceptual data-device hash is proposed to locate maliciously tampered image regions and identify the source camera of the received image data as a non-repudiable attestation in digital forensics. The presented image may have been either tampered or gone through benign content preserving geometric transforms or image processing operations. The proposed image hash is generated by projecting the invariant image features into a physical unclonable function (PUF)-defined Bernoulli random space. The tamper-resistant random PUF response is unique for each camera and can only be generated upon triggered by a challenge, which is provided by the image acquisition timestamp. The proposed hash is evaluated on the modified CASIA database and CMOS image sensor-based PUF simulated using 180 nm TSMC technology. It achieves a high tamper detection rate of 95.42% with the regions of tampered content successfully located, a good authentication performance of above 98.5% against standard content-preserving manipulations, and 96.25% and 90.42%, respectively, for the more challenging geometric transformations of rotation (0 ~ 360°) and scaling (scale factor in each dimension: 0.5). It is demonstrated to be able to identify the source camera with 100% accuracy and is secure against attacks on PUF.

Huffman decoding performance analysis of lossy compressed LAPAN-A3/IPB multispectral images

LAPAN-A3/IPB multispectral imager has the ability to produce realtime acquisition images anywhere in the world as long as there is X-band receiver in ground station to receive the image data. The received image data is the compressed version of the original image data, compressed by lossy algorithm of Fast-Fourier Transform and Huffman encoding. Processing of the received image data can be considered complicated in terms of decompressed image data validity and processing time needed. This research aims to develop robust decoding algorithm for LAPAN-A3/IPB multispectral image received in realtime acquisition mode from Bogor ground station. The research focuses on developing efficient method on Huffman decoding for relatively big image data by using look-up-table approach. The developed decoding algorithm has successfully produced daily LAPAN-A3/IPB realtime images with good image quality, where the results have been validated by using original images, recorded on satellite memory. However, the time processing needed for processing any single image is still poor, where 1 GB of compressed image data needs around 1 hour of processing time. Therefore, although the algorithm has been used to regularly produce daily LAPAN-A3/IPB realtime image data, the faster algorithm is needed to achieve better overall processing performance.

Efficient cooperative image transmission in one-way multi-hop sensor network

The challenging task while transmitting the high-quality images over the wireless sensor networks is to achieve the higher throughput, minimum bit error rate without compromising the image quality. As the sensor nodes have the limited processing power, designing energy efficient image transmission is another challenge in this research. This paper proposed a novel method of cooperative image transformation from the transmitter to the receiver for wireless sensor networks. We designed the methods for multi-hop one-way relayed cooperative communication model for wireless sensor networks. We believe that the cooperative communication helps to improve the efficiency of image transmission. The proposed approach focused on efficient relayed image transmission through wireless channels with optimum image quality and bit error rate performances. First, lightweight image quality improvement method was proposed at both transmitter and receiver end as images captured under various illumination conditions. Second, the proposed compressive sensing was performed using the approximation coefficient of 2D discrete wavelet transform. We utilized the wavelet denoising advantage by presenting the hybrid thresholding function. And third, use of decode–forward method at relay nodes to perform the task of decode and forward received image data block. The compressed approximation component of 2D discrete wavelet Transform is further used to apply inverse fast Fourier transform and then in modulation using quadrature phase shift keying to transmit over additive white Gaussian noise channel to relay nodes as per the standard orthogonal frequency-division multiplexing model. The simulation results claim the performance efficiency against the state-of-art methods based on mean square error, peak signal-to-noise ratio, and bit error rate.

Discrete image data transmission in heterogeneous wireless network using vertical handover mechanism

Vertical handover (VHO) plays an important role in providing seamless connectivity between heterogeneous wireless networks. The authors propose VHO mechanism using an image as dynamic discrete data for transmission and received signal strength (RSS)-based switching mechanism. The novelty of work lies in image data used for simulation, RSS calculation using free space propagation model, receive delay calculation and sample-based time series analysis of received data. Results shows that when VHO mechanism is carried out in ISM band operated devices it provides seamless connectivity between diverse communication protocols. Simulation results exhibit the continuous transmission of data and synchronisation of received image data.

Communication and control system for a 15-channel hermetic retinal prosthesis

A small, hermetic, wirelessly-controlled retinal prosthesis has been developed for pre-clinical studies in Yucatan minipigs. The device was attached conformally to the outside of the eye in the socket and received both power and data wirelessly from external sources. Based on the received image data, the prosthesis drove a subretinal thin-film polyimide array of sputtered iridium oxide stimulating electrodes. The implanted device included a hermetic titanium case containing a 15-channel stimulator and receiver chip and discrete circuit components. Feedthroughs in the hermetic case connected the chip to secondary power- and data-receiving coils, which coupled to corresponding external power and data coils driven by power amplifiers. Power was delivered by a 125 kHz carrier, and data were delivered by amplitude shift keying of a 15.5 MHz carrier at 100 kbps. Stimulation pulse strength, duration and frequency were programmed wirelessly from an external computer system. The final assembly was tested in vitro in physiological saline and in vivo in two minipigs for up to five and a half months by measuring stimulus artifacts generated by the implant's current drivers.

An efficient spatio-temporal boundary matching algorithm for video error concealment

The highly error-prone channel and limited computational power of terminal devices necessitates the implementation of robust yet simple error concealment. Error concealment techniques commonly make use of the surrounding correctly received image data or motion information for concealment. In this paper, we propose an efficient spatio-temporal boundary matching algorithm (ESTBMA) which exploits both spatial and temporal information to reconstruct the lost motion vectors (MV) and also introduces a new side smoothness measurement. The motion vector corresponding to the minimum of the distortion function is used as the estimation of motion vector of the lost block. Compared to the classical average motion vector (AVMV), median motion video (MMV) and boundary matching algorithm (BMA), simulation results show that the proposed algorithm can recover the higher quality image on both subjective visual evaluation and objective numerical metrics.

ROI-based procedures for progressive transmission of digital images: A comparison

Nowadays, problems arise when handling large-sized images (i.e. medical image such as Computed Tomographies or satellite images) of 10, 50, 100 or more Megabytes, due to the amount of time required for transmitting and displaying, this time being even worse when a narrow bandwidth transmission medium is involved (i.e. dial-up or mobile network), because the receiver must wait until the entire image has arrived. To solve this issue, progressive transmission schemes are used. These schemes allow the image sender to encode the image data in such a way that it is possible for the receiver to perform a reconstruction of the original image from the very beginning of transmission. Despite this reconstruction being, of course, partial, it is possible to improve the reconstruction on the fly, as more and more data of the original image are received. There are many progressive transmission methods available, such as it planes, TSVQ, DPCM, and, more recently, matrix polynomial interpolation, Discrete Cosine Transform (DCT, used in JPEG) and wavelets (used in JPEG 2000). However, none of them is well suited, or perform poorly, when, in addition to progressive transmission, we want to include also ROIs (Region Of Interest) handling. In the progressive transmission of ROIs, we want not only to reconstruct the image as we receive image data, but also to be able to select which part or parts of the emerging image we think are relevant and want to receive first, and which part or parts are of no interest. In this context we present an algorithm for lossy adaptive encoding based on singular value decomposition (SVD). This algorithm turns out to be well suited for progressive transmission and ROI selection of 2D and 3D images, as it is able to avoid redundancy in data transmission and does not require any sort of data recodification, even if we select arbitrary ROIs on the fly. We compare the performing of SVD with DCT and wavelets and show the results.

A continuous available (CA) server for medical imaging applications 1

Rationale and objectives The trend of medical imaging research and application is toward large database management and manipulation, which requires a robust image server to receive image data from sources and to deliver them to users reliably and in a timely fashion. This article describes the design, implementation, and clinical applications of a continuous available (CA) image server for these purposes. Materials and methods The design of the CA image server is based on the concept of a triple modular redundancy server with three redundant server modules. Coupled with a majority voting mechanism in the three modules and failover software, the triple modular redundancy server takes care of all single points of failure hardware components in the CA image server automatically to achieve fault tolerance. Methods and procedures of evaluating the fault tolerance system reliability caused by network connectivity, motherboard, and disk storage failures are described. Results Thorough experimental results in laboratory and clinical environments verify that the image server achieves 99.999% hardware up time (or 5 minutes/year down time), satisfying the industrial terminology of hardware continuous availability. Performance of failover of the CA image server is automatically tabulated during these procedures. Conclusion Applications of CA image server are extensive. Two examples are given including Picture Archiving and Communication System, and off-site back-up archive using the Application Service Provider model. As designed, the CA image server is portable, scalable, affordable, easy to install, and requires no human intervention during failover and system recovery.

Case study: robotic person following using fuzzy control and image segmentation

AbstractThe paper proposes a scheme for amobile robot to follow a person in reasonably complex dynamic environments. The scheme consists of an image processing technique for person identification, and a fuzzy controller for following the person. The identification process utilizes image color, shape characteristics, and a region growing technique. The fuzzy logic controller receives image data such as the mass, center of mass, and their rates of change to produce steering and speed commands for the robot. A behavior control strategy is also incorporated to cope with several situations, such as hazard, that are not accounted for in the fuzzy controller. Descriptions of the software/hardware as well as experimental setup and results are provided to demonstrate the feasibility of the scheme. © 2003 Wiley Periodicals, Inc.

PC-controlled laser diode system application

This paper presents a system with a personal-computer (PC)-controlled laser-diode beam to make film exposures for generating 256 gray-level images. The hardware equipment of this system includes an IBM PC, an 8255 interface card, and an XY table. Control software is developed to receive image data from commercially available software, such as PAINT SHOP, then convert them to signals for the laser diode and XY table. The gray level of each pixel (picture element) in an image file is represented by an 8-bit binary number. Two ways of control are demonstrated. One way uses this 8-bit number as a parameter for timing delay when the laser diode is on with a constant power output. The other way uses this 8-bit number to go through a D/A converter to control the laser diode for outputting beams with varying intensity. This way may gain higher operation speed, but requires extra hardware. There are two potential applications for this system. One is direct image exposure of yellow, magenta, cyan, and black for all image processing software data outputs, as long as their format is available. The other is for an educational training program to demonstrate the technologies of integrating computer, laser, and color printing.