A robust forgery detection method for copy-move and splicing attacks in images
- Authors: Islam, Mohammad , Karmakar, Gour , Kamruzzaman, Joarder , Murshed, Manzur
- Date: 2020
- Type: Text , Journal article
- Relation: Electronics Vol. 9, no. 9 (2020), p. 1-22
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- Description: Internet of Things (IoT) image sensors, social media, and smartphones generate huge volumes of digital images every day. Easy availability and usability of photo editing tools have made forgery attacks, primarily splicing and copy-move attacks, effortless, causing cybercrimes to be on the rise. While several models have been proposed in the literature for detecting these attacks, the robustness of those models has not been investigated when (i) a low number of tampered images are available for model building or (ii) images from IoT sensors are distorted due to image rotation or scaling caused by unwanted or unexpected changes in sensors' physical set-up. Moreover, further improvement in detection accuracy is needed for real-word security management systems. To address these limitations, in this paper, an innovative image forgery detection method has been proposed based on Discrete Cosine Transformation (DCT) and Local Binary Pattern (LBP) and a new feature extraction method using the mean operator. First, images are divided into non-overlapping fixed size blocks and 2D block DCT is applied to capture changes due to image forgery. Then LBP is applied to the magnitude of the DCT array to enhance forgery artifacts. Finally, the mean value of a particular cell across all LBP blocks is computed, which yields a fixed number of features and presents a more computationally efficient method. Using Support Vector Machine (SVM), the proposed method has been extensively tested on four well known publicly available gray scale and color image forgery datasets, and additionally on an IoT based image forgery dataset that we built. Experimental results reveal the superiority of our proposed method over recent state-of-the-art methods in terms of widely used performance metrics and computational time and demonstrate robustness against low availability of forged training samples.
- Description: This research was funded by Research Priority Area (RPA) scholarship of Federation University Australia.
Pre-trained language models with limited data for intent classification
- Authors: Kasthuriarachchy, Buddhika , Chetty, Madhu , Karmakar, Gour , Walls, Darren
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: 2020 International Joint Conference on Neural Networks, IJCNN 2020
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- Description: Intent analysis is capturing the attention of both the industry and academia due to its commercial and noncommercial significance. The rapid growth of unstructured data of micro-blogging platforms, such as Twitter and Facebook, are amongst the important sources for intent analysis. However, the social media data are often noisy and diverse, thus making the task very challenging. Further, the intent analysis frequently suffers from lack of sufficient data because the labeled datasets are often manually annotated. Recently, BERT (Bidirectional Encoder Representation from Transformers), a state-of-the-art language representation model, has attracted attention for accurate language modelling. In this paper, we investigate the application of BERT for its suitability for intent analysis. We study the fine-tuning of the BERT model through inductive transfer learning and investigate methods to overcome the challenges due to limited data availability by proposing a novel semantic data augmentation approach. This technique generates synthetic sentences while preserving the label-compatibility using the semantic meaning of the sentences, to improve the intent classification accuracy. Thus, based on the considerations for finetuning and data augmentation, a systematic and novel step-bystep methodology is presented for applying the linguistic model BERT for intent classification with limited data available. Our results show that the pre-trained language can be effectively used with noisy social media data to achieve state-of-the-art accuracy in intent analysis under low labeled-data regime. Moreover, our results also confirm that the proposed text augmentation technique is effective in eliminating noisy synthetic sentences, thereby achieving further performance improvements. © 2020 IEEE.
Trustworthiness of self-driving vehicles for intelligent transportation systems in industry applications
- Authors: Chowdhury, Abdullahi , Karmakar, Gour , Kamruzzaman, Joarder , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Informatics Vol. 17, no. 2 (2021), p. 961-970
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- Description: To enhance industrial production and automation, rapid and faster transportation of raw materials and finished products to and from distributed factories, warehouses and outlets are essential. To reduce cost with increased efficiency, this will increasingly see the use of connected and self-driving commercial vehicles fitted with industrial grade sensors on roads, shared with normal and self-driving passenger vehicles. For its wide adoption, the trustworthiness of self-driving vehicles in the intelligent transportation system (ITS) is pivotal. In this article, we introduce a novel model to measure the overall trustworthiness of a self-driving vehicle considering on-Board unit (OBU) components, GPS data and safety messages. In calculating the trustworthiness of individual OBU components, CertainLogic and beta distribution function (BDF) are used. Those trust values are fused using both the dempster-Shafer Theory (DST) and a logical operator of CertainLogic. Results of our simulation show that our proposed method can effectively determine the trust of self-driving vehicles. © 2005-2012 IEEE.
Texture as pixel feature for video object segmentation
- Authors: Ahmed, Rakib , Karmakar, Gour , Dooley, Laurence
- Date: 2008
- Type: Text , Journal article
- Relation: Electronics Letters Vol. 44, no. 19 (2008), p. 1126-1127
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Bezier curve-based generic shape encoder
- Authors: Sohel, Ferdous , Karmakar, Gour , Dooley, Laurence , Bennamoun, M.
- Date: 2010
- Type: Text , Journal article
- Relation: IET Image Processing Vol. 4, no. 2 (2010), p. 92-102
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- Description: Existing Bezier curve-based shape description techniques primarily focus upon determining a set of pertinent control points (CP) to represent a particular shape contour. While many different approaches have been proposed, none adequately consider domain-specific information about the shape contour like its gradualness and sharpness, in the CP generation process which can potentially result in large distortions in the object's shape representation. This study introduces a novel Bezier curve-based generic shape encoder (BCGSE) that partitions an object contour into contiguous segments based upon its cornerity, before generating the CP for each segment using relevant shape curvature information. In addition, although CP encoding has generally been ignored, BCGSE embeds an efficient vertex-based encoding strategy exploiting the latent equidistance between consecutive CP. A non-linear optimisation technique is also presented to enable the encoder is automatically adapt to bit-rate constraints. The performance of the BCGSE framework has been rigorously tested on a variety of diverse arbitrary shapes from both a distortion and requisite bit-rate perspective, with qualitative and quantitative results corroborating its superiority over existing shape descriptors.
Image-dependent spatial shape-error concealment
- Authors: Sohel, Ferdous , Karmakar, Gour , Dooley, Laurence
- Date: 2008
- Type: Text , Conference paper
- Relation: Signal Processing, 2008. ICSP 2008. 9th International Conference
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- Description: Existing spatial shape-error concealment techniques are broadly based upon either parametric curves that exploit geometric information concerning a shapepsilas contour or object shape statistics using a combination of Markov random fields and maximum a posteriori estimation. Both categories are to some extent, able to mask errors caused by information loss, provided the shape is considered independently of the image/video. They palpably however, do not afford the best solution in applications where shape is used as metadata to describe image and video content. This paper presents a novel image-dependent spatial shape-error concealment (ISEC) algorithm that uses both image and shape information by employing the established rubber-band contour detecting function, with the novel enhancement of automatically determining the optimal width of the band to achieve superior error concealment. Experimental results qualitatively and numerically corroborate the enhanced performance of the new ISEC strategy compared with established shape-based concealment techniques.
Reliable and energy efficient backup clustering scheme for wireless sensor networks
- Authors: Sadat, Anwar , Karmakar, Gour , Zaslavsky, Arkady , Gaber, Mohamed
- Date: 2010
- Type: Text , Conference paper
- Relation: International Conference on Information Networking 2010 p. 248-253
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- Description: Cluster-based routing protocols for wireless sensor networks have proved to be a very popular and effective innovation. They are inherently energy efficient and scalable owing to the distributed nature and hierarchical organization of sensor nodes, as well as the use of cluster heads in data reception, aggregation and transmission. However, their reliability is very limited because of the potential for sudden break down and the traffic congestion in a cluster head. A wireless communication link is also vulnerable to interference and noise. In addition, to form an optimal cluster is a NP hard problem. These problems make it very challenging to improve the reliability and energy efficiency simultaneously. To address these issues, this thesis proposes a number of clusterbased routing protocols that consider many challenging issues, such as the cluster number determination, the inter-cluster communication cost, the link quality and traffic congestion during the node clustering phase. This thesis contributes four innovative methods that improve both the reliability and energy efficiency of a wireless sensor network simultaneously. The first of these contributions is an optimum backup clustering technique, which reduces the re-clustering overhead of the network and safeguard a cluster head node from sudden break down. The second method, reliable and energy efficient inter-cluster communication, reduces the chance of a cluster head breakdown by developing routing paths that consider the optimal inter-cluster communication cost. This method also considers data loss due to poor link quality and congestion at the CH node. The third method, optimum cluster number determination technique for uniform wireless sensor network, integrates the wireless link quality factor analytically for estimating the optimal cluster number to be used in any suitable clustering protocol. Finally, joint optimization of number and allocation of clusters is introduced, which calculates the optimum cluster number at the time of node clustering. This is applicable in a wireless sensor network with both uniform and non-uniform node distributions. The performance of all the proposed methods is evaluated along with the computational complexity analysis and message overhead. To check whether the method promotes a sustainable environment, performance analysis of the backup clustering scheme has been presented for a certain portion of sensor nodes equipped with a solar cell. Statistical tests confirm that the new clustering methods exhibit significant improvements in terms of both reliability and energy efficiency over the most popular contemporary clustering protocols (e.g. HEED and only one existing backup clustering technique) with the comparable computational complexity and message overhead.
Predicting protein protein interfaces as clusters of optimal docking area points
- Authors: Arafat, Yasir , Kamruzzaman, Joarder , Karmakar, Gour , Fernandez-Recio, Juan
- Date: 2009
- Type: Text , Journal article
- Relation: International Journal of data mining and bioinformatics Vol. 3, no. 1 (2009), p. 55-67
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- Description: Abstract: Desolvation property is used here to predict protein-protein binding sites exploiting the fact that lower-valued 'optimal docking area' ODA (Fernandez-Recio et al., 2005) points form cluster at the interface. The proposed method involves two steps; clustering the ODA points and representing ODA points by average ODA values. On 51 nonredundant proteins, results show the success rate improved considerably. Considering only significant ODA, the previous ODA method has obtained a success rate of 65% with overall success rate of 39%. The proposed method improved the overall success rate to 61%. Further, comparable results were found for X-ray and NMR structures.
Detection and separation of generic-shaped objects by fuzzy clustering
- Authors: Ali, Mohammad , Karmakar, Gour , Dooley, Laurence
- Date: 2010
- Type: Text , Journal article
- Relation: International Journal of Intelligent Computing and Cybernetics Vol. 3, no. 3 (2010 2010), p. 365-390
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- Description: Image segmentation involves the separation of mutually exclusive regions/objects of interest (Gonzalez and Woods, 2002), and is integral to the image processing, coding and interpretation domains, with examples of some of the eclectic range of applications including: image analysis, robot vision, automatic car assembly, security surveillance systems, object recognition and medical imaging (Gonzalez and Woods, 2002; Hoppner et al., 1999; Pham and Prince, 1999; Gath and Geva, 1989; Pal and Pal, 1993). As there are potentially a very large number of perceptual objects in an image, with subtle variations between them, this makes generalised object-based segmentation an especially challenging task.
An environment-aware mobility model for wireless ad hoc network
- Authors: Ahmed, Sabbir , Karmakar, Gour , Kamruzzaman, Joarder
- Date: 2010
- Type: Text , Journal article
- Relation: Computer Networks Vol. 54, no. 9 (2010), p. 1470-1489
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- Description: Simulation is a cost effective, fast and flexible alternative to test-beds or practical deployment for evaluating the characteristics and potential of mobile ad hoc networks. Since environmental context and mobility have a great impact on the accuracy and efficacy of performance measurement, it is of paramount importance how closely the mobility of a node resembles its movement pattern in a real-world scenario. The existing mobility models mostly assume either free space for deployment and random node movement or the movement pattern does not emulate real-world situation properly in the presence of obstacles because of their generation of restricted paths. This demands for the development of a node movement pattern with accurately representing any obstacle and existing path in a complex and realistic deployment scenario. In this paper, we propose a general mobility model capable of creating a more realistic node movement pattern by exploiting the concept of flexible positioning of anchors. Since the model places anchors depending upon the context of the environment through which nodes are guided to move towards the destination, it is capable of representing any terrain realistically. Furthermore, obstacles of arbitrary shapes with or without doorways and any existing pathways in full or part of the terrain can be incorporated which makes the simulation environment more realistic. A detailed computational complexity has been analyzed and the characteristics of the proposed mobility model in the presence of obstacles in a university campus map with and without signal attenuation are presented which illustrates its significant impact on performance evaluation of wireless ad hoc networks.
Predicting mobile tourists
- Authors: Matthew, Michael , Karmakar, Gour , Kamruzzaman, Joarder
- Date: 2009
- Type: Text , Conference proceedings
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Video coding for mobile communications
- Authors: Sohel, Ferdous , Karmakar, Gour , Dooley, Laurence
- Date: 2008
- Type: Text , Book chapter
- Relation: Mobile Multimedia Communications: Concepts, Applications, and Challenges p. 109-150
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Fuzzy clustering for image segmentation using generic shape information
- Authors: Ali, Mohammad , Karmakar, Gour , Dooley, Laurence
- Date: 2008
- Type: Text , Journal article
- Relation: Malaysian Journal of Computer Science Vol. 21, no. 2 (2008), p. 122-138
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- Description: The performance of clustering algorithms for image segmentation are highly sensitive to the features used and types of objects in the image, which ultimately limits their generalization capability. This provides strong motivation to investigate integrating shape information into the clustering framework to improve the generality of these algorithms. Existing shape-based clustering techniques mainly focus on circular and elliptical clusters and so are unable to segment arbitrarily-shaped objects. To address this limitation, this paper presents a new shape-based algorithm called fuzzy clustering for image segmentation using generic shape information (FCGS), which exploits the B-spline representation of an object’s shape in combination with the Gustafson-Kessel clustering algorithm. Qualitative and quantitative results for FCGS confirm its superior segmentation performance consistently compared to well-established shape-based clustering techniques, for a wide range of test images comprising various regular and arbitrary-shaped objects
Dynamic bandwidth access to cognitive radio ad hoc networks through pricing modeling
- Authors: Hassan, Md Rafiul , Karmakar, Gour , Kamruzzaman, Joarder
- Date: 2011
- Type: Text , Conference paper
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- Description: Spectrum resources are becoming more and more congested as the number of wireless devices are increasing and becoming ubiquitous. Cognitive radios or secondary users (SUs) can provide the solution for better spectrum availability, bandwidth and economic aspects for both the primary service providers and the SUs. We propose a pricing model for spectrum sharing in a single level market where the primary service providers can trade spectrum with the secondary service providers. The proposed pricing model incorporates the reliability of the primary service providers and allowable coverage area, quality of the signal along with the pricing and spectrum bandwidth availability. An iterative distributed algorithm is used to reach the market equilibrium so that both the primary and the secondary service providers are satisfied with the allocated spectrum bandwidth and negotiated price. The performance of the proposed model is demonstrated using extensive numerical results with the stability analysis in reaching the market equilibrium.
Geometric distortion measurement for shape coding: a contemporary review
- Authors: Sohel, Ferdous , Karmakar, Gour , Dooley, Laurence , Bennamoun, M.
- Date: 2011
- Type: Text , Journal article
- Relation: ACM Computing Surveys Vol. 43, no. 4 (2011), p. 1-22
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- Description: Geometric distortion measurement and the associated metrics involved are integral to the Rate Distortion (RD) shape coding framework, with importantly the efficacy of the metrics being strongly influenced by the underlying measurement strategy. This has been the catalyst for many different techniques with this article presenting a comprehensive review of geometric distortion measurement, the diverse metrics applied, and their impact on shape coding. The respective performance of these measuring strategies is analyzed from both a RD and complexity perspective, with a recent distortion measurement technique based on arc-length-parameterization being comparatively evaluated. Some contemporary research challenges are also investigated, including schemes to effectively quantify shape deformation.
Quasi-Bezier curves integrating localised information
- Authors: Sohel, Ferdous , Karmakar, Gour , Dooley, Laurence , Arkinstall, John
- Date: 2008
- Type: Text , Journal article
- Relation: Pattern Recognition Vol. 41, no. 2 (2008), p. 531-542
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- Description: Bezier curves (BC) have become fundamental tools in many challenging and varied applications, ranging from computer-aided geometric design to generic object shape descriptors. A major limitation of the classical Bezier curve, however, is that only global information about its control points (CP) is considered, so there can often be a large gap between the curve and its control polygon, leading to large distortion in shape representation. While strategies such as degree elevation, composite BC, refinement and subdivision reduce this gap, they also increase the number of CP and hence bit-rate, and computational complexity. This paper presents novel contributions to BC theory, with the introduction of quasi-Bezier curves (QBC), which seamlessly integrate localised CP information into the inherent global Bezier framework, with no increase in either the number of CP or order of computational complexity. QBC crucially retains the core properties of the classical BC, such as geometric continuity and affine invariance, and can be embedded into the vertex-based shape coding and shape descriptor framework to enhance rate-distortion performance. The performance of QBC has been empirically tested upon a number of natural and synthetically shaped objects, with both qualitative and quantitative results confirming its consistently superior approximation performance in comparison with both the classical BC and other established BC-based shape descriptor methods.
Introduction to mobile multimedia communications
- Authors: Karmakar, Gour , Dooley, Laurence , Mathew, Michael
- Date: 2008
- Type: Text , Book chapter
- Relation: Mobile Multimedia Communications: Concepts, Applications, and Challenge p. 1-23
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Optimal reliable and energy aware inter-cluster communication in wireless sensor networks
- Authors: Sadat, Anwar , Karmakar, Gour
- Date: 2010
- Type: Text , Conference proceedings
- Full Text: false
- Description: Inter-cluster communication technique is drawing immense research interest in recent wireless sensor network (WSN) applications. Since sensor nodes are very much constrained in power supply, extending lifetime of these sensors is essential. On the other hand, it is difficult to provide reliable data transfer in WSNs because of their unreliable link quality and congestion at a cluster head (CH) node. CHs perform the crucial inter-cluster communication task for WSN. However, extreme use of energy due to relaying multi-hop data traffic leads to sudden death of a CH node. Existing routing protocols usually utilize minimum hop count or energy consumption path for inter-cluster path selection; consequently, they ignore the reliability in the routing process. In this paper, we have proposed an optimal inter-cluster routing technique considering both energy consumption and reliability. Reliability is measured in terms of link quality and congestion that mainly introduce data loss. Simulation results demonstrate that the proposed technique has improved both network lifetime and reliability significantly compared with the contemporary cluster based routing techniques.
Delay-aware query routing tree for wireless sensor networks
- Authors: Pervin, Shaila , Kamruzzaman, Joarder , Karmakar, Gour
- Date: 2012
- Type: Text , Conference paper
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- Description: Timeliness in query response is the major quality metric for query processing in the real-time applications of Wireless Sensor Networks (WSNs). The structure of the query routing tree directly affects the whole query processing delay as it provides the path to forward a query to the relevant nodes and return the response to the sink. In the current literature, query routing structure is designed irrespective of the variation in query loads among the sensors. As a consequence, current schemes do not guarantee for the routing tree to provide a faster path to the sensors with higher query load. This motivates the current work to consider query load in constructing and self-reconfiguring the routing tree. In this paper, we present a query load-based spanning tree construction method that reduces the query response delay as well as energy consumption in query execution and provides query response with the best possible accuracy. Simulation results illustrate the efficacy of the proposed framework.
Sliding-window designs for vertex-based shape coding
- Authors: Sohel, Ferdous , Karmakar, Gour , Dooley, Laurence , Bennamoun, M.
- Date: 2012
- Type: Text , Journal article
- Relation: IEEE Transactions on Multimedia Vol. 14, no. 3 (June 2012), p. 683-692
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- Description: Traditionally the sliding window (SW) has been employed in vertex-based operational rate distortion (ORD) optimal shape coding algorithms to ensure consistent distortion (quality) measurement and improve computational efficiency. It also regulates the memory requirements for an encoder design enabling regular, symmetrical hardware implementations. This paper presents a series of new enhancements to existing techniques for determining the best SW-length within a rate-distortion (RD) framework, and analyses the nexus between SW-length and storage for ORD hardware realizations. In addition, it presents an efficient bit-allocation strategy for managing multiple shapes together with a generalized adaptive SW scheme which integrates localized curvature information (cornerity) on contour points with a bi-directional spatial distance, to afford a superior and more pragmatic SW design compared with existing adaptive SW solutions which are based on only cornerity values. Experimental results consistently corroborate the effectiveness of these new strategies.