Imagery makes up a large percentage of geospatial data in use today. One feature of this imagery is that it tends to be large, often hundreds or thousands of megabytes. As a result JPEG compression is often used to make geospatial imagery manageable by reducing the file size without greatly reducing the quality of the image. However, the benefits of compression are absent when the image must be viewed. Viewing a large JPEG image requires decompressing and holding the uncompressed version in memory. Holding the entirety of a large image in memory is a burden on many systems and sometimes impossible. However, the entire image is rarely needed at full resolution. Usually only a small area of interest is viewed or processed. This paper describes a method of removing a small area of interest from a large JPEG without decompressing the entire image. JPEG compressed images are streams which cannot be randomly accessed. Viewing a particular area requires that all preceding areas be partially decompressed. This process is more efficient than fully decompressing the whole JPEG, but depending on the area requested the entire image may need to be partially decompressed. To circumvent this problem an index file is created on first decompression which records markers for the sections of the JPEG. The index file allows random access to the JPEG file so that areas may be decompressed without reading the preceding portions of the JPEG. This method of decompressing a JPEG requires a limited amount of memory and with an index file is fast enough to be performed in real time.
Mobile Phones and other hand held devices are constrained in their memory and computational power, and yet new generations of theses devices provide access to the web-based services and are equipped with digital cameras that make them more attractive to users. These added capabilities are expected to help incorporate such devices into the global communication system. In order to take advantage of these capabilities, there are desperate need for highly efficient algorithms including real-time image and video processing and transmission. This paper is concerned with high quality video compression for constrained mobile devices. We attempt to tweak a wavelet-based feature-preserving image compression technique that we have developed recently, so as to make it suitable for implementation on mobile phones and PDA's. The earlier version of the compression algorithm exploits the statistical properties of the multi-resolution wavelet-transformed images. The main modification is based on the observation that in many cases the statistical parameters of wavelet subbands of adjacent video frames do not differ significantly. We shall investigate the possibility of re-using codebooks for a sequence of adjacent frames without having adverse effect on image quality if any. Such an approach results in significant bandwidth and processing-time savings. The performance of this scheme will be tested in comparison to other video compression methods. Such a scheme is expected to be of use in security applications such as transmission of biometric data for a server-based verification.
Compression ideas are applied to the design of exceedingly fast SAR imagery clutter covariance processors for use in knowledge-aided (KA) airborne moving target indicator (AMTI) radar subjected to severely taxing disturbances. Outstanding signal to interference plus noise ratio (SINR) radar performance is derived with radar-blind highly compressed SAR imagery.
In this paper it is found that the outstanding memory space compression achieved with predictive-transform (PT) source coding is not affected by its integration with a very fast and simple bit planes methodology that operates on the quantized coefficient errors emanating from the 'lossy' PT source encoder section. It is shown, in particular, that the technique outperforms wavelets based JPEG2000 by more than 5 dBs when it compresses by a factor of 8,192 a test synthetic aperture radar (SAR) image used in knowledge-aided airborne moving target indicator (AMTI) radar.
Steganalysis has many challenges; which include the accurate and efficient detection of hidden content within digital images. This paper focuses on the development of a new multi pixel comparison method used for the detection of steganographic content within digital images transmitted over mobile channels. The sensitivity of detecting hidden information within a digital image can be increased or decreased to determine if slight changes have been made to the digital image for the target of blind steganalysis. The key thought of the presented method is to increase the sensitivity of features when alterations are made within the bit planes of a digital image. The differences between the new method and existing pixel comparison methods are; multiple masks of different sizes are used to increase the sensitivity and weighted features are used to improve the classification of the feature sets. Weights are also used with the various pixel comparisons to ensure proper sensitivity when detecting small changes. The article also investigates the reliability of detection and estimation length of hidden data within wireless digital images with potential for military applications emphasizing on defense and security.
The paper presents a Digital Image Processing toolbox for cellular phones. It is intended for users dealing with imaging algorithms and allows the processing of real images taken by the camera phones. For example, users are able to analyze the images and selected regions of interest using different transforms including Discrete Fourier, Hartley, and Cosine Transforms. One can apply different filters such as median and moving average. Simple image enhancement techniques are also included in the toolbox. A handy user interface allows a suitable browsing through the images and operators. The toolbox is designed to be expandable and more operations will be included in the future targeting military and security applications. The toolbox is implemented using Series 60 Platform SDK for Symbiantm OS, for C++. It allows developers to quickly and efficiently run and test applications for devices that are compatible with the Series 60 Platform. The algorithms are first implemented on Series 60 Platform device emulator on the PC and then installed on the cell phone.
This paper presents a novel method for edge detection within two-dimensional signals (images). Using Boolean partial derivatives calculated quickly through a logical transform, the algorithm generates a binary edge map. The process is initially described for binary data and then extended for multi-bit (grayscale) images. Computer simulations demonstrate the procedure for three classes of signals: synthetic images (where actual edge maps are known), natural images, and cell-phone images (those taken by a low-resolution, low-quality camera). Results are compared quantitatively (when possible with Pratt's figure of merit) and visually with six common edge detection techniques: Sobel, Prewitt, Roberts, Laplacian of Gaussian, zero-cross and Canny methods. Comparison with these methods demonstrates that the algorithm presented here is able to consistently perform competitively in the numerical sense, while also detecting major edges and fine details simultaneously. Both of these latter aspects are visually apparent in the binary output image maps produced.
This article presents an overview of the SecurePhone project, with an account of the first results obtained.
SecurePhone's primary aim is to realise a mobile phone prototype - the 'SecurePhone' - in which biometrical
authentication enables users to deal secure, dependable transactions over a mobile network. The SecurePhone is based
on a commercial PDA-phone, supplemented with specific software modules and a customised SIM card. It integrates in
a single environment a number of advanced features: access to cryptographic keys through strong multimodal biometric
authentication; appending and verification of digital signatures; real-time exchange and interactive modification of (esigned)
documents and voice recordings. SecurePhone's 'biometric recogniser' is based on original research. A fused
combination of three different biometric methods - speaker, face and handwritten signature verification - is exploited,
with no need for dedicated hardware components. The adoption of non-intrusive, psychologically neutral biometric
techniques is expected to mitigate rejection problems that often inhibit the social use of biometrics, and speed up the
spread of e-signature technology. Successful biometric authentication grants access to SecurePhone's built-in esignature
services through a user-friendly interface. Special emphasis is accorded to the definition of a trustworthy
security chain model covering all aspects of system operation.
The SecurePhone is expected to boost m-commerce and open new scenarios for m-business and m-work, by changing
the way people interact and by improving trust and confidence in information technologies, often considered
intimidating and difficult to use. Exploitation plans will also explore other application domains (physical and logical
access control, securised mobile communications).
The rise of international terrorism and the rapid increase in fraud and identity theft has added urgency to the
task of developing biometric-based person identification as a reliable alternative to conventional authentication
methods. Human Identification based on face images is a tough challenge in comparison to identification based
on fingerprints or Iris recognition. Yet, due to its unobtrusive nature, face recognition is the preferred method
of identification for security related applications. The success of such systems will depend on the support of
massive infrastructures. Current mobile communication devices (3G smart phones) and PDA's are equipped
with a camera which can capture both still and streaming video clips and a touch sensitive display panel. Beside
convenience, such devices provide an adequate secure infrastructure for sensitive & financial transactions, by
protecting against fraud and repudiation while ensuring accountability. Biometric authentication systems for
mobile devices would have obvious advantages in conflict scenarios when communication from beyond enemy
lines is essential to save soldier and civilian life. In areas of conflict or disaster the luxury of fixed infrastructure
is not available or destroyed. In this paper, we present a wavelet-based face verification scheme that have been
specifically designed and implemented on a currently available PDA. We shall report on its performance on the
benchmark audio-visual BANCA database and on a newly developed PDA recorded audio-visual database that
take include indoor and outdoor recordings.
A GMM based audio visual speaker verification system is described and an Active Appearance Model with a linear speaker transformation system is used to evaluate the robustness of the verification. An Active Appearance Model (AAM) is used to automatically locate and track a speaker's face in a video recording. A Gaussian Mixture Model (GMM) based classifier (BECARS) is used for face verification. GMM training and testing is accomplished on DCT based extracted features of the detected faces. On the audio side, speech features are extracted and used for speaker verification with the GMM based classifier. Fusion of both audio and video modalities for audio visual speaker verification is compared with face verification and speaker verification systems.
To improve the robustness of the multimodal biometric identity verification system, an audio visual imposture system is envisioned. It consists of an automatic voice transformation technique that an impostor may use to assume the identity of an authorized client. Features of the transformed voice are then combined with the corresponding appearance features and fed into the GMM based system BECARS for training. An attempt is made to increase the acceptance rate of the impostor and to analyzing the robustness of the verification system.
Experiments are being conducted on the BANCA database, with a prospect of experimenting on the newly developed PDAtabase developed within the scope of the SecurePhone project.
Person authentication can be strongly enhanced by the combination of different modalities. This is also true for the face and voice signals, which can be obtained with minimal inconvenience for the user. However, features from each modality can be combined at various different levels of processing and for face and voice signals the advantage of fusion depends strongly on the way they are combined. The aim of the work presented is to investigate the optimal strategy for combining voice and face modalities for signals of varying quality. The experimental data are taken from a newly acquired database using a PDA, which contains audio-visual recordings in different conditions. Voice features use mel-frequency cepstral coefficients, while the face signal is parameterised using wavelet coefficients in certain subbands. Results are presented for both early (feature-level) and late (score-level) fusion. At each level different fixed and variable weightings are used, both to weight between frames within each modality and to weight between modalities, where weights are based on some measure of signal reliability, such as the accuracy of automatic face detection or the audio signal to noise ratio. In addition, the contribution to authentication of information from different areas of the face is explored to determine a regional weighting for the face coefficients.
Verification of a person's identity by the combination of more than one biometric trait strongly increases the robustness of person authentication in real applications. This is particularly the case in applications involving signals of degraded quality, as for person authentication on mobile platforms. The context of mobility generates degradations of input signals due to the variety of environments encountered (ambient noise, lighting variations, etc.), while the sensors' lower quality further contributes to decrease in system performance. Our aim in this work is to combine traits from the three biometric modalities of speech, face and handwritten signature in a concrete application, performing non intrusive biometric verification on a personal mobile device (smartphone/PDA).
Most available biometric databases have been acquired in more or less controlled environments, which makes it difficult to predict performance in a real application. Our experiments are performed on a database acquired on a PDA as part of the SecurePhone project (IST-2002-506883 project "Secure Contracts Signed by Mobile Phone"). This database contains 60 virtual subjects balanced in gender and age. Virtual subjects are obtained by coupling audio-visual signals from real English speaking subjects with signatures from other subjects captured on the touch screen of the PDA. Video data for the PDA database was recorded in 2 recording sessions separated by at least one week. Each session comprises 4 acquisition conditions: 2 indoor and 2 outdoor recordings (with in each case, a good and a degraded quality recording). Handwritten signatures were captured in one session in realistic conditions. Different scenarios of matching between training and test conditions are tested to measure the resistance of various fusion systems to different types of variability and different amounts of enrolment data.
Adaptive steganography, an intelligent approach to message hiding, integrated with matrix encoding and pn-sequences serves as a promising resolution to recent security assurance concerns. Incorporating the above data hiding concepts with established cryptographic protocols in wireless communication would greatly increase the security and privacy of transmitting sensitive information. We present an algorithm which will address the following problems: 1) low embedding capacity in mobile devices due to fixed image dimensions and memory constraints, 2) compatibility between mobile and land based desktop computers, and 3) detection of stego images by widely available steganalysis software [1-3]. Consistent with the smaller available memory, processor capabilities, and limited resolution associated with mobile devices, we propose a more magnified approach to steganography by focusing adaptive efforts at the pixel level. This deeper method, in comparison to the block processing techniques commonly found in existing adaptive methods, allows an increase in capacity while still offering a desired level of security. Based on computer simulations using high resolution, natural imagery and mobile device captured images, comparisons show that the proposed method securely allows an increased amount of embedding capacity but still avoids detection by varying steganalysis techniques.
Currently, cellular phones constitute a significant portion of the global telecommunications market. Modern cellular phones offer sophisticated features such as Internet access, on-board cameras, and expandable memory which provide these devices with excellent multimedia capabilities. Because of the high volume of cellular traffic, as well as the ability of these devices to transmit nearly all forms of data. The need for an increased level of security in wireless communications is becoming a growing concern. Steganography could provide a solution to this important problem.
In this article, we present a new algorithm for JPEG-compressed images which is applicable to mobile platforms. This algorithm embeds sensitive information into quantized discrete cosine transform coefficients obtained from the cover JPEG. These coefficients are rearranged based on certain statistical properties and the inherent processing and memory constraints of mobile devices. Based on the energy variation and block characteristics of the cover image, the sensitive data is hidden by using a switching embedding technique proposed in this article. The proposed system offers high capacity while simultaneously withstanding visual and statistical attacks.
Based on simulation results, the proposed method demonstrates an improved retention of first-order statistics when compared to existing JPEG-based steganographic algorithms, while maintaining a capacity which is comparable to F5 for certain cover images.
Multimedia transports in wireless, ad-hoc, multi-hop or mobile networks must be capable of obtaining information about the network and adaptively tune sending and encoding parameters to the network response. Obtaining meaningful metrics to guide a stable congestion control mechanism in the transport (i.e. passive, simple, end-to-end and network technology independent) is a complex problem. Equally difficult is obtaining a reliable QoS metrics that agrees with user perception in a client/server or distributed environment. Existing metrics, objective or subjective, are commonly used after or before to test or report on a transmission and require access to both original and transmitted frames. In this paper, we propose that an efficient and successful video delivery and the optimization of overall network QoS requires innovation in a) a direct measurement of available and bottleneck capacity for its congestion control and b) a meaningful subjective QoS metric that is dynamically reported to video sender. Once these are in place, a binomial -stable, fair and TCP friendly- algorithm can be used to determine the sending rate and other packet video parameters. An adaptive mpeg codec can then continually test and fit its parameters and temporal-spatial data-error control balance using the perceived QoS dynamic feedback. We suggest a new measurement based on a packet dispersion technique that is independent of underlying network mechanisms. We then present a binomial control based on direct measurements. We implement a QoS metric that is known to agree with user perception (MPQM) in a client/server, distributed environment by using predetermined table lookups and characterization of video content.
For secure mobile wireless networks whose topologies are changed dynamically in insecure environments, mobile users
need to keep in contact with each other for the purpose of user authentications. For instance, the network formed by a
group of soldiers equipped with wireless devices in a battlefield. Maintaining a high connectivity is crucial in such
networks in order to authenticate scattered individuals and to be able to communicate with each other. To establish
connections, different mobile ad hoc network routing protocols have been developed. However, much research has
shown that these protocols are incapable of maintaining high connectivity when the node density is lower in the
network. This paper proposes a mechanism to enhance the node connectivity, which is specifically effective for mobile
ad hoc networks with lower node densities. It selects some nodes with larger transmission power as strategic nodes to
assist in establishing connections with remote nodes, which are unable to connect with otherwise. The strategic nodes
have the ability to connect with each other. Whenever a remote mobile node has a request to connect to another remote
mobile node, the strategic nodes function as normal mobile nodes and may forward the connection requests to the
desired remote destination node. The mechanism is simulated in different scenarios with various node densities, and the
results show that the node connectivity is generally enhanced with the benefit of lower node density network, gaining
We present in this paper an integrated robust image transmission scheme using space-time block codes (STBC) over
multi-input multi-output (MIMO) wireless systems. First, in order to achieve an excellent error resilient capability,
multiple bitstreams are generated based on wavelet trees along the spatial orientations. The spatial-orientation trees in the
wavelet domain are individually encoded using SPIHT. Error propagation is thus limited within each bitstreams. Then,
Reed-Solomon (R-S) codes as forward error correction (FEC) are adopted to combat transmission errors over error-prone
wireless channels and to detect residual errors so as to avoid error propagation in each bitstream. FEC can reduce the bit
error rates at the expenses of increased data rate. However, it is often difficult to design an optimal FEC scheme for a
time-varying multi-path fading channel that may fluctuate beyond the capacity of the adopted FEC scheme. Therefore, in
order to overcome such difficulty, we propose an approach to alleviate the effect of multi-path fading by employing the
STBC for spatial diversity with assumption that channel state information (CSI) is perfectly estimated at the receiver.
Experimental results demonstrate that the proposed scheme can achieve much improved performance in terms of PSNR
over Rayleigh flat fading channel as compared with a wireless system without spatial diversity.
The mathematical theory of signal processing, named processor coding, will be shown to inherently arise as the computational time dual of Shannon's mathematical theory of communication which is also known as source coding. Source coding is concerned with signal source memory space compression while processor coding deals with signal processor computational time compression. Their combination is named compression-designs and referred as Conde in short. A compelling and pedagogically appealing diagram will be discussed highlighting Conde's remarkable successful application to real-world knowledge-aided (KA) airborne moving target indicator (AMTI) radar.
Wireless ad hoc networking offers convenient infrastructureless communication over the shared wireless channel. However, the nature of ad hoc networks makes them vulnerable to security attacks. Unlike their wired counterpart, infrastructureless ad hoc networks do not have a clear line of defense, their topology is dynamically changing, and every mobile node can receive messages from its neighbors and can be contacted by all other nodes in its neighborhood. This poses a great danger to network security if some nodes behave in a malicious manner. The immediate concern about the security in this type of networks is how to protect the network and the individual mobile nodes against malicious act of rogue nodes from within the network. This paper is concerned with security aspects of wireless ad hoc networks. We shall present results of simulation experiments on ad hoc network's performance in the presence of malicious nodes. We shall investigate two types of attacks and the consequences will be simulated and quantified in terms of loss of packets and other factors. The results show that network performance, in terms of successful packet delivery ratios, significantly deteriorates when malicious nodes act according to the defined misbehaving characteristics.
A secure image transmission scheme based on JPEG2000 codec is proposed in this paper, which combines encryption with encoding and is suitable for real-time applications. In this scheme, the sensitive data are self-authenticated, then partial-encrypted during compression process, and the compressed data are encrypted by the lightweight encryption algorithm combined with error-correction codec. The self-authentication process can detect malicious tampering or transmission errors. The encryption process obtains suitable tradeoff between security and time-efficiency through encrypting data adaptively, and keeps the original system's error-robustness. The decryption process is symmetric to the encryption process. Experimental results show that this scheme obtains high perception security and time efficiency, and is thus suitable for secure image transmission over network.
In this paper, we address the problem privacy in video surveillance. We propose an efficient solution based on transformdomain
scrambling of regions of interest in a video sequence. More specifically, the sign of selected transform
coefficients is flipped during encoding. We address more specifically the case of Motion JPEG 2000. Simulation results
show that the technique can be successfully applied to conceal information in regions of interest in the scene while
providing with a good level of security. Furthermore, the scrambling is flexible and allows adjusting the amount of
distortion introduced. This is achieved with a small impact on coding performance and negligible computational
complexity increase. In the proposed video surveillance system, heterogeneous clients can remotely access the system
through the Internet or 2G/3G mobile phone network. Thanks to the inherently scalable Motion JPEG 2000 codestream,
the server is able to adapt the resolution and bandwidth of the delivered video depending on the usage environment of the
An algorithm for object segmentation from stereo sequences based on fusion of multi-cues of edge, disparity, motion and color is presented in this paper. Firstly, the accurate disparity field is obtained using a two-level disparity matching method based on image edge information. The morphological operators are then performed on the given disparity field to obtain coarse objects segments. "Split and merge" process is applied to extract the objects regions, and "erosion and dilation" process is used to fill some small inner holes in the target regions or smooth the discontinuous regions. On the other hand, spatial-temporal segments are obtained with image edge structure and motion change detection. Different object boundaries can be articulated according to disparity and spatial-temporal segments. At last, the multi-objects are extracted by further fusion of the color information. Experiments indicate this algorithm is an effective method for segmenting multi-objects overlapped each other from stereoscopic video that usually is difficult to be done in the case of monocular video.
Image enhancement performance is currently judged subjectively, with no reliable manner of quantifying the results of an enhancement. Current quantitative measures rely on linear algorithms to determine contrast, leaving room for improvement. With the introduction of more complex enhancement algorithms, there is a need for an effective method of quantifying performance to select optimal parameters. In this paper, we present a logarithmic based image enhancement measure. We demonstrate its performance on real world images. The results will show the effectiveness of our measures to select optimal enhancement parameters for the enhancement algorithms.
Biometric databases form an essential tool in the fight against international terrorism, organised crime and fraud. Various
government and law enforcement agencies have their own biometric databases consisting of combination of fingerprints,
Iris codes, face images/videos and speech records for an increasing number of persons. In many cases personal data
linked to biometric records are incomplete and/or inaccurate. Besides, biometric data in different databases for the same
individual may be recorded with different personal details. Following the recent terrorist atrocities, law enforcing
agencies collaborate more than before and have greater reliance on database sharing. In such an environment, reliable
biometric-based identification must not only determine who you are but also who else you are. In this paper we propose a
compact content-based video signature and indexing scheme that can facilitate retrieval of multiple records in face
biometric databases that belong to the same person even if their associated personal data are inconsistent. We shall assess
the performance of our system using a benchmark audio visual face biometric database that has multiple videos for each
subject but with different identity claims. We shall demonstrate that retrieval of relatively small number of videos that are
nearest, in terms of the proposed index, to any video in the database results in significant proportion of that individual
Skilled Support Personnel (SSP) serve emergency response organizations during an emergency incident, and include laborers, operating engineers, carpenters, ironworkers, sanitation workers and utility workers. SSP called to an emergency incident rarely have recent detailed training on the chemical, biological, radiological, nuclear and/or explosives (CBRNE) agents or the personal protection equipment (PPE) relevant to the incident. This increases personal risk to the SSP and mission risk at the incident site. Training for SSP has been identified as a critical need by the National Institute for Environmental Health Sciences, Worker Education and Training Program. We present a system being developed to address this SSP training shortfall by exploiting a new training paradigm called just-in-time training (JITT) made possible by advances in distance learning and cellular telephony. In addition to the current conventional training at regularly scheduled instructional events, SSP called to an emergency incident will have secure access to short (<5 minutes) training modules specific to the incident and derived from the Occupational Safety and Health Administration (OSHA) Disaster Site Worker Course. To increase retention, each learning module incorporates audio, video, interactive simulations, graphics, animation, and assessment designed for the user interface of most current cell phones. Engineering challenges include compatibility with current cell phone technologies and wireless service providers, integration with the incident management system, and SCORM compliance.