Search results for: CMOS image sensor

Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

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Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel. The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. Message Passing Interface (MPI) and Open Computing Language (OpenCL) is used to achieve task and pixel level parallelism respectively.

Keywords: Edge detection, multicore, GPU, openCL, MPI.

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Authors: N. Chaitawittanun, M. Munlin

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Due to rapid advancement of powerful image processing software, digital images are easy to manipulate and modify by ordinary people. Lots of digital images are edited for a specific purpose and more difficult to distinguish form their original ones. We propose a clustering method to detect a copy-move image forgery of JPEG, BMP, TIFF, and PNG. The process starts with reducing the color of the photos. Then, we use the clustering technique to divide information of measuring data by Hausdorff Distance. The result shows that the purposed methods is capable of inspecting the image file and correctly identify the forgery.

Keywords: Image detection, forgery image, copy-paste.

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Authors: Mohsen A. M. El-Bendary, Mostafa A. R. El-Tokhy

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This paper presents an efficient burst error spreading tool. Also, it studies a vital issue in wireless communications, which is the transmission of images over wireless networks. IEEE ZigBee 802.15.4 is a short-range communication standard that could be used for small distance multimedia transmissions. In fact, the ZigBee network is a Wireless Personal Area Network (WPAN), which needs a strong interleaving mechanism for protection against error bursts. Also, it is low power technology and utilized in the Wireless Sensor Networks (WSN) implementation. This paper presents the chaotic interleaving scheme as a data randomization tool for this purpose. This scheme depends on the chaotic Baker map. The mobility effects on the image transmission are studied with different velocity through utilizing the Jakes’ model. A comparison study between the proposed chaotic interleaving scheme and the traditional block and convolutional interleaving schemes for image transmission over a correlated fading channel is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes.

Keywords: WPANs, Burst Errors, Mobility, Interleaving Techniques, Fading channels.

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Authors: Moslem Afrashteh Mehr

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Wireless Sensor Networks consist of small battery powered devices with limited energy resources. once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, One of the most important issues that needs to be enhanced in order to improve the life span of the network is energy efficiency. to overcome this demerit many research have been done. The clustering is the one of the representative approaches. in the clustering, the cluster heads gather data from nodes and sending them to the base station. In this paper, we introduce a dynamic clustering algorithm using genetic algorithm. This algorithm takes different parameters into consideration to increase the network lifetime. To prove efficiency of proposed algorithm, we simulated the proposed algorithm compared with LEACH algorithm using the matlab

Keywords: Wireless Sensor Networks, Clustering, Geneticalgorithm, Energy Consumption

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Authors: Mona F. M. Mursi, Ghazy M.R. Assassa, Hatim A. Aboalsamh, Khaled Alghathbar

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The challenge in the case of image authentication is that in many cases images need to be subjected to non malicious operations like compression, so the authentication techniques need to be compression tolerant. In this paper we propose an image authentication system that is tolerant to JPEG lossy compression operations. A scheme for JPEG grey scale images is proposed based on a data embedding method that is based on a secret key and a secret mapping vector in the frequency domain. An encrypted feature vector extracted from the image DCT coefficients, is embedded redundantly, and invisibly in the marked image. On the receiver side, the feature vector from the received image is derived again and compared against the extracted watermark to verify the image authenticity. The proposed scheme is robust against JPEG compression up to a maximum compression of approximately 80%,, but sensitive to malicious attacks such as cutting and pasting.

Keywords: Authentication, DCT, JPEG, Watermarking.

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Authors: M. Sangeetha, A. Sabari, T. Shanthi Priya

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Recent advances in wireless networking technologies introduce several energy aware routing protocols in sensor networks. Such protocols aim to extend the lifetime of network by reducing the energy consumption of nodes. Many researchers are looking for certain challenges that are predominant in the grounds of energy consumption. One such protocol that addresses this energy consumption issue is ‘Cluster based hierarchical routing protocol’. In this paper, we intend to discuss some of the major hierarchical routing protocols adhering towards sensor networks. Furthermore, we examine and compare several aspects and characteristics of few widely explored hierarchical clustering protocols, and its operations in wireless sensor networks (WSN). This paper also presents a discussion on the future research topics and the challenges of hierarchical clustering in WSNs.

Keywords: Clustering, Energy Efficiency, Hierarchical routing, Wireless sensor networks.

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Authors: S. Anna Durai, E. Anna Saro

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Image Compression using Artificial Neural Networks is a topic where research is being carried out in various directions towards achieving a generalized and economical network. Feedforward Networks using Back propagation Algorithm adopting the method of steepest descent for error minimization is popular and widely adopted and is directly applied to image compression. Various research works are directed towards achieving quick convergence of the network without loss of quality of the restored image. In general the images used for compression are of different types like dark image, high intensity image etc. When these images are compressed using Back-propagation Network, it takes longer time to converge. The reason for this is, the given image may contain a number of distinct gray levels with narrow difference with their neighborhood pixels. If the gray levels of the pixels in an image and their neighbors are mapped in such a way that the difference in the gray levels of the neighbors with the pixel is minimum, then compression ratio as well as the convergence of the network can be improved. To achieve this, a Cumulative distribution function is estimated for the image and it is used to map the image pixels. When the mapped image pixels are used, the Back-propagation Neural Network yields high compression ratio as well as it converges quickly.

Keywords: Back-propagation Neural Network, Cumulative Distribution Function, Correlation, Convergence.

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

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In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, nonreferencequality measures, objective quality measures.

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Authors: Malka N. Halgamuge, Toong-Khuan Chan, Priyan Mendis

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Monitoring and automatic control of building environment is a crucial application of Wireless Sensor Network (WSN) in which maximizing network lifetime is a key challenge. Previous research into the performance of a network in a building environment has been concerned with radio propagation within a single floor. We investigate the link quality distribution to obtain full coverage of signal strength in a four-storey building environment, experimentally. Our results indicate that the transitional region is of particular concern in wireless sensor network since it accommodates high variance unreliable links. The transitional region in a multi-storey building is mainly due to the presence of reinforced concrete slabs at each storey and the fac┬©ade which obstructs the radio signal and introduces an additional absorption term to the path loss.

Keywords: Wireless sensor networks, radio propagation, building monitoring

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Authors: Kuo-Yang Cheng, Yi-Lun Pan, Chang-Hsing Wu, His-En Yu, Hui-Shan Chen, Weicheng Huang

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The main mission of Ezilla is to provide a friendly interface to access the virtual machine and quickly deploy the high performance computing environment. Ezilla has been developed by Pervasive Computing Team at National Center for High-performance Computing (NCHC). Ezilla integrates the Cloud middleware, virtualization technology, and Web-based Operating System (WebOS) to form a virtual computer in distributed computing environment. In order to upgrade the dataset and speedup, we proposed the sensor observation system to deal with a huge amount of data in the Cassandra database. The sensor observation system is based on the Ezilla to store sensor raw data into distributed database. We adopt the Ezilla Cloud service to create virtual machines and login into virtual machine to deploy the sensor observation system. Integrating the sensor observation system with Ezilla is to quickly deploy experiment environment and access a huge amount of data with distributed database that support the replication mechanism to protect the data security.

Keywords: Cloud, Virtualization, Cassandra, WebOS

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Authors: Hamed Vahdat Nejad, Hossein Deldari

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Wavelet transforms are multiresolution decompositions that can be used to analyze signals and images. Image compression is one of major applications of wavelet transforms in image processing. It is considered as one of the most powerful methods that provides a high compression ratio. However, its implementation is very time-consuming. At the other hand, parallel computing technologies are an efficient method for image compression using wavelets. In this paper, we propose a parallel wavelet compression algorithm based on quadtrees. We implement the algorithm using MatlabMPI (a parallel, message passing version of Matlab), and compute its isoefficiency function, and show that it is scalable. Our experimental results confirm the efficiency of the algorithm also.

Keywords: Image compression, MPI, Parallel computing, Wavelets.

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Authors: H. AbdelRahman, S. Rostom, Y. Lotfy, S. Salah Eldeen, R. Yassein, N. Awny

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People are growing more concerned with their appearance in today's society. But they are terrified of what they will look like after a plastic surgery. People's mental health suffers when they have accidents, burns, or genetic issues that cause them to cleave certain body parts, which makes them feel uncomfortable and unappreciated. The method provides an innovative deep learning-based technique for image inpainting that analyzes different picture structures and fixes damaged images. This study proposes a model based on the Stable Diffusion Inpainting method for in-painting medical images. One significant advancement made possible by deep neural networks is image inpainting, which is the process of reconstructing damaged and missing portions of an image. The patient can see the outcome more easily since the system uses the user's input of an image to identify a problem. It then modifies the image and outputs a fixed image.

Keywords: Generative Adversarial Network, GAN, Large Mask Inpainting, LAMA, Stable Diffusion Inpainting.

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Authors: Yi-an Cui, Lu Wang, Jian-ping Xiao

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This paper presents an automatic feature recognition method based on center-surround difference detecting and fuzzy logic that can be applied in ground-penetrating radar (GPR) image processing. Adopted center-surround difference method, the salient local image regions are extracted from the GPR images as features of detected objects. And fuzzy logic strategy is used to match the detected features and features in template database. This way, the problem of objects detecting, which is the key problem in GPR image processing, can be converted into two steps, feature extracting and matching. The contributions of these skills make the system have the ability to deal with changes in scale, antenna and noises. The results of experiments also prove that the system has higher ratio of features sensing in using GPR to image the subsurface structures.

Keywords: feature recognition, GPR image, matching strategy, salient image

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Authors: Hyo-Nam Song

Abstract:

The changes in quality properties and nutritional components in two fermented mugworts (Artemisia capillaries Thumberg, Artemisiaeasiaticae Nakai) were characterized followed by the rapid pattern analysis of volatile flavor compounds by Electric Nose based on SAW(Surface Acoustic Wave) sensor in GC system. There were remarkable decreases in the pH and small changes in the total soluble solids after fermentation. The L (lightness) and b (yellowness) values in Hunter's color system were shown to be decreased, whilst the a (redness) value was increased by fermentation. The HPLC analysis demonstrated that total amino acids were increased in quantity and the essential amino acids were contained higher in A. asiaticaeNakai than in A. capillaries Thumberg. While the total polyphenol contents were not affected by fermentation, the total sugar contents were dramatically decreased. Scopoletinwere highly abundant in A. capillarisThumberg, however, it was not detected in A. asiaticaeNakai. Volatile flavor compounds by Electric Nose showed that the intensity of several peaks were increased much and seven additional flavor peaks were newly produced after fermentation. The flavor differences of two mugworts were clearly distinguished from the image patterns of VaporPrintTM which indicate that the fermentation enables the two mugworts to have subtle flavor differences.

Keywords: Mugwort, Fermentation, Electric Nose, SAW sensor, Flavor.

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Authors: F. Amin, A. H. Jahangir, H. Rasifard

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With the widespread growth of applications of Wireless Sensor Networks (WSNs), the need for reliable security mechanisms these networks has increased manifold. Many security solutions have been proposed in the domain of WSN so far. These solutions are usually based on well-known cryptographic algorithms. In this paper, we have made an effort to survey well known security issues in WSNs and study the behavior of WSN nodes that perform public key cryptographic operations. We evaluate time and power consumption of public key cryptography algorithm for signature and key management by simulation.

Keywords: Wireless Sensor Networks, Security, Public Key Cryptography, Key Management.

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Authors: Md. Asif Jahangir Chowdhury, Md. Shahriar Rizwan, M. S. Islam

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In CMOS integrated circuit design there is a trade-off between static power consumption and technology scaling. Recently, the power density has increased due to combination of higher clock speeds, greater functional integration, and smaller process geometries. As a result static power consumption is becoming more dominant. This is a challenge for the circuit designers. However, the designers do have a few methods which they can use to reduce this static power consumption. But all of these methods have some drawbacks. In order to achieve lower static power consumption, one has to sacrifice design area and circuit performance. In this paper, we propose a new method to reduce static power in the CMOS VLSI circuit using Variable Body Biasing technique without being penalized in area requirement and circuit performance.

Keywords: variable body biasing, state saving technique, stack effect, dual V-th, static power reduction.

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Authors: Say Wei Foo, Qi Dong

Abstract:

Digital watermarking is one of the techniques for copyright protection. In this paper, a normalization-based robust image watermarking scheme which encompasses singular value decomposition (SVD) and discrete cosine transform (DCT) techniques is proposed. For the proposed scheme, the host image is first normalized to a standard form and divided into non-overlapping image blocks. SVD is applied to each block. By concatenating the first singular values (SV) of adjacent blocks of the normalized image, a SV block is obtained. DCT is then carried out on the SV blocks to produce SVD-DCT blocks. A watermark bit is embedded in the highfrequency band of a SVD-DCT block by imposing a particular relationship between two pseudo-randomly selected DCT coefficients. An adaptive frequency mask is used to adjust local watermark embedding strength. Watermark extraction involves mainly the inverse process. The watermark extracting method is blind and efficient. Experimental results show that the quality degradation of watermarked image caused by the embedded watermark is visually transparent. Results also show that the proposed scheme is robust against various image processing operations and geometric attacks.

Keywords: Image watermarking, Image normalization, Singularvalue decomposition, Discrete cosine transform, Robustness.

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Authors: Fatih Kara, Cabir Vural

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In this work, a special case of the image superresolution problem where the only type of motion is global translational motion and the blurs are shift-invariant is investigated. The necessary conditions for exact reconstruction of the original image by using finite impulse-response reconstruction filters are developed. Given that the conditions are satisfied, a method for exact super-resolution is presented and some simulation results are shown.

Keywords: Image processing, image super-resolution, finite impulse-response filters, existence-uniqueness conditions.

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Authors: Morteza Fathipour, Samira Omidbakhsh, Kimia Khodayari

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RF performance of SOI CMOS device has attracted significant amount of interest recently. In order to improve RF parameters, Strained Si/Relaxed Si0.8Ge0.2 investigated as a replacement for Si technology .Enhancement of carrier mobility associated with strain engineering makes Strained Si a promising candidate for improving RF performance of CMOS technology. From the simulation, the cut-off frequency is estimated to be 224 GHZ, whereas in SOI at similar bias is about 188 GHZ. Therefore, Strained Si exhibits 19% improvement in cut-off frequency over similar Si counterpart. In this paper, Ion/Ioff ratio is studied as one of the key parameters in logic and digital application. Strained Si/SiGe demonstrates better Ion/Ioff characteristic than SOI, in similar channel length of 100 nm.Another important key analog figures of merit such as Early Voltage (VEA) ,transconductance vs drain current (gm /Ids) are studied. They introduce the efficiency of the devices to convert dc power into ac frequency.

Keywords: cut-off frequency, RF application, Silicon oninsulator, Strained Si/SiGe on insulator.

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Authors: Safaa Al-Ali, Ahmad Shahin, Fadi Chakik

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Image coding based on clustering provides immediate access to targeted features of interest in a high quality decoded image. This approach is useful for intelligent devices, as well as for multimedia content-based description standards. The result of image clustering cannot be precise in some positions especially on pixels with edge information which produce ambiguity among the clusters. Even with a good enhancement operator based on PDE, the quality of the decoded image will highly depend on the clustering process. In this paper, we introduce an ambiguity cluster in image coding to represent pixels with vagueness properties. The presence of such cluster allows preserving some details inherent to edges as well for uncertain pixels. It will also be very useful during the decoding phase in which an anisotropic diffusion operator, such as Perona-Malik, enhances the quality of the restored image. This work also offers a comparative study to demonstrate the effectiveness of a fuzzy clustering technique in detecting the ambiguity cluster without losing lot of the essential image information. Several experiments have been carried out to demonstrate the usefulness of ambiguity concept in image compression. The coding results and the performance of the proposed algorithms are discussed in terms of the peak signal-tonoise ratio and the quantity of ambiguous pixels.

Keywords: Ambiguity Cluster, Anisotropic Diffusion, Fuzzy Clustering, Image Compression.

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Authors: T. Kumaresan, S. Sanjushree, C. Palanisamy

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Image spam is a kind of email spam where the spam text is embedded with an image. It is a new spamming technique being used by spammers to send their messages to bulk of internet users. Spam email has become a big problem in the lives of internet users, causing time consumption and economic losses. The main objective of this paper is to detect the image spam by using histogram properties of an image. Though there are many techniques to automatically detect and avoid this problem, spammers employing new tricks to bypass those techniques, as a result those techniques are inefficient to detect the spam mails. In this paper we have proposed a new method to detect the image spam. Here the image features are extracted by using RGB histogram, HSV histogram and combination of both RGB and HSV histogram. Based on the optimized image feature set classification is done by using k- Nearest Neighbor(k-NN) algorithm. Experimental result shows that our method has achieved better accuracy. From the result it is known that combination of RGB and HSV histogram with k-NN algorithm gives the best accuracy in spam detection.

Keywords: File Type, HSV Histogram, k-NN, RGB Histogram, Spam Detection.

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Authors: Hadi Veisi, Mansour Jamzad

Abstract:

In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation are evaluated and compared. In training and evaluation, each image block is assigned to a network based on its complexity value. Best-SNR is another alternative in selecting compressor network for image blocks in evolution phase which chooses one of the trained networks such that results best SNR in compressing the input image block. In our evaluations, best results are obtained when overlapping the blocks is allowed and choosing the networks in compressor is based on the Best-SNR. In this case, the results demonstrate superiority of this method comparing with previous similar works and JPEG standard coding.

Keywords: Adaptive image compression, Image complexity, Multi-layer perceptron neural network, JPEG Standard, PSNR.

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Authors: Mahinda P. Pathegama, Özdemir Göl

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Extraction of edge-end-pixels is an important step for the edge linking process to achieve edge-based image segmentation. This paper presents an algorithm to extract edge-end pixels together with their directional sensitivities as an augmentation to the currently available mathematical models. The algorithm is implemented in the Java environment because of its inherent compatibility with web interfaces since its main use is envisaged to be for remote image analysis on a virtual instrumentation platform.

Keywords: edge-end pixels, image processing, imagesegmentation, pixel extraction

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Authors: Peter Rothenpieler, Daniela Kruger, Dennis Pfisterer, Stefan Fischer, Denise Dudek, Christian Haas, Martina Zitterbart

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In the project FleGSens, a wireless sensor network (WSN) for the surveillance of critical areas and properties is currently developed which incorporates mechanisms to ensure information security. The intended prototype consists of 200 sensor nodes for monitoring a 500m long land strip. The system is focused on ensuring integrity and authenticity of generated alarms and availability in the presence of an attacker who may even compromise a limited number of sensor nodes. In this paper, two of the main protocols developed in the project are presented, a tracking protocol to provide secure detection of trespasses within the monitored area and a protocol for secure detection of node failures. Simulation results of networks containing 200 and 2000 nodes as well as the results of the first prototype comprising a network of 16 nodes are presented. The focus of the simulations and prototype are functional testing of the protocols and particularly demonstrating the impact and cost of several attacks.

Keywords: Wireless Sensor Network, Security, Trespass Detection, Testbed.

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Authors: A. H. W. Goh, Y. S. Yong, C. H. Chan, S. J. Then, L. P. Chu, S. W. Chau, H. W. Hon

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This paper proposes an alternative control mechanism for an interactive Pan/Tilt/Zoom (PTZ) camera control system. Instead of using a mouse or a joystick, the proposed mechanism utilizes a Nintendo Wii remote and infrared (IR) sensor bar. The Wii remote has buttons that allows the user to control the movement of a PTZ camera through Bluetooth connectivity. In addition, the Wii remote has a built-in motion sensor that allows the user to give control signals to the PTZ camera through pitch and roll movement. A stationary IR sensor bar, placed at some distance away opposite the Wii remote, enables the detection of yaw movement. In addition, the Wii remote-s built-in IR camera has the ability to detect its spatial position, and thus generates a control signal when the user moves the Wii remote. Some experiments are carried out and their performances are compared with an industry-standard PTZ joystick.

Keywords: Bluetooth, Infrared, Pan/Tilt/Zoom, PTZ Camera, Visual Surveillance, Wii Remote

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

Abstract:

In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: Augmented reality framework, server-client model, vision-based tracking, image search.

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Authors: Ruchika, Munish Vashisht, S. Qamar

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Detection of small ship is crucial task in many automatic surveillance systems which are employed for security of maritime boundaries of a country. To address this problem, image de-noising is technique to identify the target ship in between many other ships in the sea. Image de-noising technique needs to extract the ship’s image from sea background for the analysis as the ship’s image may submerge in the background and flooding waves. In this paper, a noise filter is presented that is based on fuzzy linguistic ‘most’ quantifier. Ordered weighted averaging (OWA) function is used to remove salt-pepper noise of ship’s image. Results obtained are in line with the results available by other well-known median filters and OWA based approach shows better performance.

Keywords: Linguistic quantifier, impulse noise, OWA filter, median filter.

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Authors: R.Sukesh Kumar, Abhisek Verma, Jasprit Singh

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In this work a novel approach for color image segmentation using higher order entropy as a textural feature for determination of thresholds over a two dimensional image histogram is discussed. A similar approach is applied to achieve multi-level thresholding in both grayscale and color images. The paper discusses two methods of color image segmentation using RGB space as the standard processing space. The threshold for segmentation is decided by the maximization of conditional entropy in the two dimensional histogram of the color image separated into three grayscale images of R, G and B. The features are first developed independently for the three ( R, G, B ) spaces, and combined to get different color component segmentation. By considering local maxima instead of the maximum of conditional entropy yields multiple thresholds for the same image which forms the basis for multilevel thresholding.

Keywords: conditional entropy, multi-level thresholding, segmentation, two dimensional image histogram

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Authors: Ashish Payal, C. S. Rai, B. V. R. Reddy

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With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m² grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.

Keywords: Localization, wireless sensor networks, artificial neural network, radial basis function, multi-layer perceptron, backpropagation, RSSI.

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Authors: K. Sakthivel, R. Nallusamy, C. Kavitha

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The system is designed to show images which are related to the query image. Extracting color, texture, and shape features from an image plays a vital role in content-based image retrieval (CBIR). Initially RGB image is converted into HSV color space due to its perceptual uniformity. From the HSV image, Color features are extracted using block color histogram, texture features using Haar transform and shape feature using Fuzzy C-means Algorithm. Then, the characteristics of the global and local color histogram, texture features through co-occurrence matrix and Haar wavelet transform and shape are compared and analyzed for CBIR. Finally, the best method of each feature is fused during similarity measure to improve image retrieval effectiveness and accuracy.

Keywords: Color Histogram, Haar Wavelet Transform, Fuzzy C-means, Co-occurrence matrix; Similarity measure.

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