Search results for: T.O.F.D Image (Time of Flight Diffraction).
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8079

Search results for: T.O.F.D Image (Time of Flight Diffraction).

7689 Analysis of Patterns in TV Commercials that Recognize NGO Image

Authors: J. Areerut, F. Samuel

Abstract:

The purpose of this research is to analyze the pattern of television commercials and how they encourage non-governmental organizations to build their image in Thailand. It realizes how public relations can impact an organization's image. It is a truth that bad public relations management can cause hurt a reputation. On the other hand, a very small amount of work in public relations helps your organization to be recognized broadly and eventually accepted even wider. The main idea in this paper is to study and analyze patterns of television commercials that could impact non-governmental organization's images in a greater way. This research uses questionnaires and content analysis to summarize results. The findings show the aspects of how patterns of television commercials that are suited to non-governmental organization work in Thailand. It will be useful for any non-governmental organization that wishes to build their image through television commercials and also for further work based on this research.

Keywords: Television Commercial (TVC), Organization Image, Non-Governmental Organization: NGO, Public Relation.

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7688 A Comparison of Image Data Representations for Local Stereo Matching

Authors: André Smith, Amr Abdel-Dayem

Abstract:

The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: Colour data, local stereo matching, stereo correspondence, disparity map.

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7687 Performance Analysis of Chrominance Red and Chrominance Blue in JPEG

Authors: Mamta Garg

Abstract:

While compressing text files is useful, compressing still image files is almost a necessity. A typical image takes up much more storage than a typical text message and without compression images would be extremely clumsy to store and distribute. The amount of information required to store pictures on modern computers is quite large in relation to the amount of bandwidth commonly available to transmit them over the Internet and applications. Image compression addresses the problem of reducing the amount of data required to represent a digital image. Performance of any image compression method can be evaluated by measuring the root-mean-square-error & peak signal to noise ratio. The method of image compression that will be analyzed in this paper is based on the lossy JPEG image compression technique, the most popular compression technique for color images. JPEG compression is able to greatly reduce file size with minimal image degradation by throwing away the least “important" information. In JPEG, both color components are downsampled simultaneously, but in this paper we will compare the results when the compression is done by downsampling the single chroma part. In this paper we will demonstrate more compression ratio is achieved when the chrominance blue is downsampled as compared to downsampling the chrominance red in JPEG compression. But the peak signal to noise ratio is more when the chrominance red is downsampled as compared to downsampling the chrominance blue in JPEG compression. In particular we will use the hats.jpg as a demonstration of JPEG compression using low pass filter and demonstrate that the image is compressed with barely any visual differences with both methods.

Keywords: JPEG, Discrete Cosine Transform, Quantization, Color Space Conversion, Image Compression, Peak Signal to Noise Ratio & Compression Ratio.

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7686 Fuzzy Based Visual Texture Feature for Psoriasis Image Analysis

Authors: G. Murugeswari, A. Suruliandi

Abstract:

This paper proposes a rotational invariant texture feature based on the roughness property of the image for psoriasis image analysis. In this work, we have applied this feature for image classification and segmentation. The fuzzy concept is employed to overcome the imprecision of roughness. Since the psoriasis lesion is modeled by a rough surface, the feature is extended for calculating the Psoriasis Area Severity Index value. For classification and segmentation, the Nearest Neighbor algorithm is applied. We have obtained promising results for identifying affected lesions by using the roughness index and severity level estimation.

Keywords: Fuzzy texture feature, psoriasis, roughness feature, skin disease.

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7685 National Image in the Age of Mass Self-Communication: An Analysis of Internet Users' Perception of Portugal

Authors: L. Godinho, N. Teixeira

Abstract:

Nowadays, massification of Internet access represents one of the major challenges to the traditional powers of the State, among which the power to control its external image. The virtual world has also sparked the interest of social sciences which consider it a new field of study, an immense open text where sense is expressed. In this paper, that immense text has been accessed to so as to understand the perception Internet users from all over the world have of Portugal. Ours is a quantitative and qualitative approach, as we have resorted to buzz, thematic and category analysis. The results confirm the predominance of sea stereotype in others' vision of the Portuguese people, and evidence that national image has adapted to network communication through processes of individuation and paganization.

Keywords: Internet, national image, perception, web analytics.

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7684 FPGA Hardware Implementation and Evaluation of a Micro-Network Architecture for Multi-Core Systems

Authors: Yahia Salah, Med Lassaad Kaddachi, Rached Tourki

Abstract:

This paper presents the design, implementation and evaluation of a micro-network, or Network-on-Chip (NoC), based on a generic pipeline router architecture. The router is designed to efficiently support traffic generated by multimedia applications on embedded multi-core systems. It employs a simplest routing mechanism and implements the round-robin scheduling strategy to resolve output port contentions and minimize latency. A virtual channel flow control is applied to avoid the head-of-line blocking problem and enhance performance in the NoC. The hardware design of the router architecture has been implemented at the register transfer level; its functionality is evaluated in the case of the two dimensional Mesh/Torus topology, and performance results are derived from ModelSim simulator and Xilinx ISE 9.2i synthesis tool. An example of a multi-core image processing system utilizing the NoC structure has been implemented and validated to demonstrate the capability of the proposed micro-network architecture. To reduce complexity of the image compression and decompression architecture, the system use image processing algorithm based on classical discrete cosine transform with an efficient zonal processing approach. The experimental results have confirmed that both the proposed image compression scheme and NoC architecture can achieve a reasonable image quality with lower processing time.

Keywords: Generic Pipeline Network-on-Chip Router Architecture, JPEG Image Compression, FPGA Hardware Implementation, Performance Evaluation.

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7683 Image Transmission via Iterative Cellular-Turbo System

Authors: Ersin Gose, Kenan Buyukatak, Onur Osman, Osman N. Ucan

Abstract:

To compress, improve bit error performance and also enhance 2D images, a new scheme, called Iterative Cellular-Turbo System (IC-TS) is introduced. In IC-TS, the original image is partitioned into 2N quantization levels, where N is denoted as bit planes. Then each of the N-bit-plane is coded by Turbo encoder and transmitted over Additive White Gaussian Noise (AWGN) channel. At the receiver side, bit-planes are re-assembled taking into consideration of neighborhood relationship of pixels in 2-D images. Each of the noisy bit-plane values of the image is evaluated iteratively using IC-TS structure, which is composed of equalization block; Iterative Cellular Image Processing Algorithm (ICIPA) and Turbo decoder. In IC-TS, there is an iterative feedback link between ICIPA and Turbo decoder. ICIPA uses mean and standard deviation of estimated values of each pixel neighborhood. It has extra-ordinary satisfactory results of both Bit Error Rate (BER) and image enhancement performance for less than -1 dB Signal-to-Noise Ratio (SNR) values, compared to traditional turbo coding scheme and 2-D filtering, applied separately. Also, compression can be achieved by using IC-TS systems. In compression, less memory storage is used and data rate is increased up to N-1 times by simply choosing any number of bit slices, sacrificing resolution. Hence, it is concluded that IC-TS system will be a compromising approach in 2-D image transmission, recovery of noisy signals and image compression.

Keywords: Iterative Cellular Image Processing Algorithm (ICIPA), Turbo Coding, Iterative Cellular Turbo System (IC-TS), Image Compression.

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7682 Extraction of Semantic Digital Signatures from MRI Photos for Image-Identification Purposes

Authors: Marios Poulos, George Bokos

Abstract:

This paper makes an attempt to solve the problem of searching and retrieving of similar MRI photos via Internet services using morphological features which are sourced via the original image. This study is aiming to be considered as an additional tool of searching and retrieve methods. Until now the main way of the searching mechanism is based on the syntactic way using keywords. The technique it proposes aims to serve the new requirements of libraries. One of these is the development of computational tools for the control and preservation of the intellectual property of digital objects, and especially of digital images. For this purpose, this paper proposes the use of a serial number extracted by using a previously tested semantic properties method. This method, with its center being the multi-layers of a set of arithmetic points, assures the following two properties: the uniqueness of the final extracted number and the semantic dependence of this number on the image used as the method-s input. The major advantage of this method is that it can control the authentication of a published image or its partial modification to a reliable degree. Also, it acquires the better of the known Hash functions that the digital signature schemes use and produces alphanumeric strings for cases of authentication checking, and the degree of similarity between an unknown image and an original image.

Keywords: Computational Geometry, MRI photos, Image processing, pattern Recognition.

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7681 Three-Dimensional Off-Line Path Planning for Unmanned Aerial Vehicle Using Modified Particle Swarm Optimization

Authors: Lana Dalawr Jalal

Abstract:

This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex threedimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.

Keywords: Obstacle Avoidance, Particle Swarm Optimization, Three-Dimensional Path Planning Unmanned Aerial Vehicles.

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7680 Investigating Polynomial Interpolation Functions for Zooming Low Resolution Digital Medical Images

Authors: Maninder Pal

Abstract:

Medical digital images usually have low resolution because of nature of their acquisition. Therefore, this paper focuses on zooming these images to obtain better level of information, required for the purpose of medical diagnosis. For this purpose, a strategy for selecting pixels in zooming operation is proposed. It is based on the principle of analog clock and utilizes a combination of point and neighborhood image processing. In this approach, the hour hand of clock covers the portion of image to be processed. For alignment, the center of clock points at middle pixel of the selected portion of image. The minute hand is longer in length, and is used to gain information about pixels of the surrounding area. This area is called neighborhood pixels region. This information is used to zoom the selected portion of the image. The proposed algorithm is implemented and its performance is evaluated for many medical images obtained from various sources such as X-ray, Computerized Tomography (CT) scan and Magnetic Resonance Imaging (MRI). However, for illustration and simplicity, the results obtained from a CT scanned image of head is presented. The performance of algorithm is evaluated in comparison to various traditional algorithms in terms of Peak signal-to-noise ratio (PSNR), maximum error, SSIM index, mutual information and processing time. From the results, the proposed algorithm is found to give better performance than traditional algorithms.

Keywords: Zooming, interpolation, medical images, resolution.

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7679 Indexing and Searching of Image Data in Multimedia Databases Using Axial Projection

Authors: Khalid A. Kaabneh

Abstract:

This paper introduces and studies new indexing techniques for content-based queries in images databases. Indexing is the key to providing sophisticated, accurate and fast searches for queries in image data. This research describes a new indexing approach, which depends on linear modeling of signals, using bases for modeling. A basis is a set of chosen images, and modeling an image is a least-squares approximation of the image as a linear combination of the basis images. The coefficients of the basis images are taken together to serve as index for that image. The paper describes the implementation of the indexing scheme, and presents the findings of our extensive evaluation that was conducted to optimize (1) the choice of the basis matrix (B), and (2) the size of the index A (N). Furthermore, we compare the performance of our indexing scheme with other schemes. Our results show that our scheme has significantly higher performance.

Keywords: Axial Projection, images, indexing, multimedia database, searching.

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7678 Quick Similarity Measurement of Binary Images via Probabilistic Pixel Mapping

Authors: Adnan A. Y. Mustafa

Abstract:

In this paper we present a quick technique to measure the similarity between binary images. The technique is based on a probabilistic mapping approach and is fast because only a minute percentage of the image pixels need to be compared to measure the similarity, and not the whole image. We exploit the power of the Probabilistic Matching Model for Binary Images (PMMBI) to arrive at an estimate of the similarity. We show that the estimate is a good approximation of the actual value, and the quality of the estimate can be improved further with increased image mappings. Furthermore, the technique is image size invariant; the similarity between big images can be measured as fast as that for small images. Examples of trials conducted on real images are presented.

Keywords: Big images, binary images, similarity, matching.

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7677 Optimization of the Dental Direct Digital Imaging by Applying the Self-Recognition Technology

Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad

Abstract:

This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.

Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts.

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7676 The Mechanistic Deconvolutive Image Sensor Model for an Arbitrary Pan–Tilt Plane of View

Authors: S. H. Lim, T. Furukawa

Abstract:

This paper presents a generalized form of the mechanistic deconvolution technique (GMD) to modeling image sensors applicable in various pan–tilt planes of view. The mechanistic deconvolution technique (UMD) is modified with the given angles of a pan–tilt plane of view to formulate constraint parameters and characterize distortion effects, and thereby, determine the corrected image data. This, as a result, does not require experimental setup or calibration. Due to the mechanistic nature of the sensor model, the necessity for the sensor image plane to be orthogonal to its z-axis is eliminated, and it reduces the dependency on image data. An experiment was constructed to evaluate the accuracy of a model created by GMD and its insensitivity to changes in sensor properties and in pan and tilt angles. This was compared with a pre-calibrated model and a model created by UMD using two sensors with different specifications. It achieved similar accuracy with one-seventh the number of iterations and attained lower mean error by a factor of 2.4 when compared to the pre-calibrated and UMD model respectively. The model has also shown itself to be robust and, in comparison to pre-calibrated and UMD model, improved the accuracy significantly.

Keywords: Image sensor modeling, mechanistic deconvolution, calibration, lens distortion

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7675 A General Framework for Knowledge Discovery Using High Performance Machine Learning Algorithms

Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: Active Contour, Bayesian, Echocardiographic image, Feature vector.

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7674 The Feasibility of Augmenting an Augmented Reality Image Card on a Quick Response Code

Authors: Alfred Chen, Shr Yu Lu, Cong Seng Hong, Yur-June Wang

Abstract:

This research attempts to study the feasibility of augmenting an augmented reality (AR) image card on a Quick Response (QR) code. The authors have developed a new visual tag, which contains a QR code and an augmented AR image card. The new visual tag has features of reading both of the revealed data of the QR code and the instant data from the AR image card. Furthermore, a handheld communicating device is used to read and decode the new visual tag, and then the concealed data of the new visual tag can be revealed and read through its visual display. In general, the QR code is designed to store the corresponding data or, as a key, to access the corresponding data from the server through internet. Those reveled data from the QR code are represented in text. Normally, the AR image card is designed to store the corresponding data in 3-Dimensional or animation/video forms. By using QR code's property of high fault tolerant rate, the new visual tag can access those two different types of data by using a handheld communicating device. The new visual tag has an advantage of carrying much more data than independent QR code or AR image card. The major findings of this research are: 1) the most efficient area for the designed augmented AR card augmenting on the QR code is 9% coverage area out of the total new visual tag-s area, and 2) the best location for the augmented AR image card augmenting on the QR code is located in the bottom-right corner of the new visual tag.

Keywords: Augmented reality, QR code, Visual tag, Handheldcommunicating device

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7673 Multi-Focus Image Fusion Using SFM and Wavelet Packet

Authors: Somkait Udomhunsakul

Abstract:

In this paper, a multi-focus image fusion method using Spatial Frequency Measurements (SFM) and Wavelet Packet was proposed. The proposed fusion approach, firstly, the two fused images were transformed and decomposed into sixteen subbands using Wavelet packet. Next, each subband was partitioned into sub-blocks and each block was identified the clearer regions by using the Spatial Frequency Measurement (SFM). Finally, the recovered fused image was reconstructed by performing the Inverse Wavelet Transform. From the experimental results, it was found that the proposed method outperformed the traditional SFM based methods in terms of objective and subjective assessments.

Keywords: Multi-focus image fusion, Wavelet Packet, Spatial Frequency Measurement.

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7672 Acid Fuchsin Dye Based PMMA Film for Holographic Investigations

Authors: G. Vinitha, A. Ramalingam

Abstract:

In view of a possible application in optical data storage devices, diffraction grating efficiency of an organic dye, Acid Fuchsin doped in PMMA matrix was studied under excitation with CW diode pumped Nd: YAG laser at 532 nm. The open aperture Zscan of dye doped polymer displayed saturable absorption and the closed aperture Z-scan of the samples exhibited negative nonlinearity. The diffraction efficiency of the grating is the ratio of the intensity of the first order diffracted power to the incident read beam power. The dye doped polymer films were found to be good media for recording. It is observed that the formation of gratings strongly depend on the concentration of dye in the polymer film, the intensity ratios of the writing beams and the angle between the writing beams. It has been found that efficient writing can be made at an angle of 20o and when the intensity ratio of the writing beams is unity.

Keywords: Diffraction efficiency, Nonlinear Optical material, saturable absorption, Surface-relief-gratings.

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7671 A Universal Model for Content-Based Image Retrieval

Authors: S. Nandagopalan, Dr. B. S. Adiga, N. Deepak

Abstract:

In this paper a novel approach for generalized image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. This is provided through User Interface (UI) in the form of relevance feedback. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture cooccurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, a novel idea is developed based on greedy strategy to reduce the computational complexity. The entire system was developed using AForge.Imaging (an open source product), MATLAB .NET Builder, C#, and Oracle 10g. The system was tested with Coral Image database containing 1000 natural images and achieved better results.

Keywords: Content Based Image Retrieval (CBIR), Cooccurrencematrix, Feature vector, Edge Histogram Descriptor(EHD), Greedy strategy.

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7670 Classification of Computer Generated Images from Photographic Images Using Convolutional Neural Networks

Authors: Chaitanya Chawla, Divya Panwar, Gurneesh Singh Anand, M. P. S Bhatia

Abstract:

This paper presents a deep-learning mechanism for classifying computer generated images and photographic images. The proposed method accounts for a convolutional layer capable of automatically learning correlation between neighbouring pixels. In the current form, Convolutional Neural Network (CNN) will learn features based on an image's content instead of the structural features of the image. The layer is particularly designed to subdue an image's content and robustly learn the sensor pattern noise features (usually inherited from image processing in a camera) as well as the statistical properties of images. The paper was assessed on latest natural and computer generated images, and it was concluded that it performs better than the current state of the art methods.

Keywords: Image forensics, computer graphics, classification, deep learning, convolutional neural networks.

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7669 On-line Image Mosaicing of Live Stem Cells

Authors: Alessandro Bevilacqua, Alessandro Gherardi, Filippo Piccinini

Abstract:

Image mosaicing is a technique that permits to enlarge the field of view of a camera. For instance, it is employed to achieve panoramas with common cameras or even in scientific applications, to achieve the image of a whole culture in microscopical imaging. Usually, a mosaic of cell cultures is achieved through using automated microscopes. However, this is often performed in batch, through CPU intensive minimization algorithms. In addition, live stem cells are studied in phase contrast, showing a low contrast that cannot be improved further. We present a method to study the flat field from live stem cells images even in case of 100% confluence, this permitting to build accurate mosaics on-line using high performance algorithms.

Keywords: Microscopy, image mosaicing, stem cells.

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7668 Image Adaptive Watermarking with Visual Model in Orthogonal Polynomials based Transformation Domain

Authors: Krishnamoorthi R., Sheba Kezia Malarchelvi P. D.

Abstract:

In this paper, an image adaptive, invisible digital watermarking algorithm with Orthogonal Polynomials based Transformation (OPT) is proposed, for copyright protection of digital images. The proposed algorithm utilizes a visual model to determine the watermarking strength necessary to invisibly embed the watermark in the mid frequency AC coefficients of the cover image, chosen with a secret key. The visual model is designed to generate a Just Noticeable Distortion mask (JND) by analyzing the low level image characteristics such as textures, edges and luminance of the cover image in the orthogonal polynomials based transformation domain. Since the secret key is required for both embedding and extraction of watermark, it is not possible for an unauthorized user to extract the embedded watermark. The proposed scheme is robust to common image processing distortions like filtering, JPEG compression and additive noise. Experimental results show that the quality of OPT domain watermarked images is better than its DCT counterpart.

Keywords: Orthogonal Polynomials based Transformation, Digital Watermarking, Copyright Protection, Visual model.

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7667 A Review on Medical Image Registration Techniques

Authors: Shadrack Mambo, Karim Djouani, Yskandar Hamam, Barend van Wyk, Patrick Siarry

Abstract:

This paper discusses the current trends in medical image registration techniques and addresses the need to provide a solid theoretical foundation for research endeavours. Methodological analysis and synthesis of quality literature was done, providing a platform for developing a good foundation for research study in this field which is crucial in understanding the existing levels of knowledge. Research on medical image registration techniques assists clinical and medical practitioners in diagnosis of tumours and lesion in anatomical organs, thereby enhancing fast and accurate curative treatment of patients. Literature review aims to provide a solid theoretical foundation for research endeavours in image registration techniques. Developing a solid foundation for a research study is possible through a methodological analysis and synthesis of existing contributions. Out of these considerations, the aim of this paper is to enhance the scientific community’s understanding of the current status of research in medical image registration techniques and also communicate to them, the contribution of this research in the field of image processing. The gaps identified in current techniques can be closed by use of artificial neural networks that form learning systems designed to minimise error function. The paper also suggests several areas of future research in the image registration.

Keywords: Image registration techniques, medical images, neural networks, optimisation, transformation.

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7666 Color Constancy using Superpixel

Authors: Xingsheng Yuan, Zhengzhi Wang

Abstract:

Color constancy algorithms are generally based on the simplified assumption about the spectral distribution or the reflection attributes of the scene surface. However, in reality, these assumptions are too restrictive. The methodology is proposed to extend existing algorithm to applying color constancy locally to image patches rather than globally to the entire images. In this paper, a method based on low-level image features using superpixels is proposed. Superpixel segmentation partition an image into regions that are approximately uniform in size and shape. Instead of using entire pixel set for estimating the illuminant, only superpixels with the most valuable information are used. Based on large scale experiments on real-world scenes, it can be derived that the estimation is more accurate using superpixels than when using the entire image.

Keywords: color constancy, illuminant estimation, superpixel

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7665 The Use of Classifiers in Image Analysis of Oil Wells Profiling Process and the Automatic Identification of Events

Authors: Jaqueline M. R. Vieira

Abstract:

Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge dataset configurations.

Keywords: Brazil, classifiers, data-mining, Image Segmentation, oil well visualization, classifiers.

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7664 Simulation Based VLSI Implementation of Fast Efficient Lossless Image Compression System Using Adjusted Binary Code & Golumb Rice Code

Authors: N. Muthukumaran, R. Ravi

Abstract:

The Simulation based VLSI Implementation of FELICS (Fast Efficient Lossless Image Compression System) Algorithm is proposed to provide the lossless image compression and is implemented in simulation oriented VLSI (Very Large Scale Integrated). To analysis the performance of Lossless image compression and to reduce the image without losing image quality and then implemented in VLSI based FELICS algorithm. In FELICS algorithm, which consists of simplified adjusted binary code for Image compression and these compression image is converted in pixel and then implemented in VLSI domain. This parameter is used to achieve high processing speed and minimize the area and power. The simplified adjusted binary code reduces the number of arithmetic operation and achieved high processing speed. The color difference preprocessing is also proposed to improve coding efficiency with simple arithmetic operation. Although VLSI based FELICS Algorithm provides effective solution for hardware architecture design for regular pipelining data flow parallelism with four stages. With two level parallelisms, consecutive pixels can be classified into even and odd samples and the individual hardware engine is dedicated for each one. This method can be further enhanced by multilevel parallelisms.

Keywords: Image compression, Pixel, Compression Ratio, Adjusted Binary code, Golumb Rice code, High Definition display, VLSI Implementation.

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7663 Quality of Non-Point Source Pollutant Identification using Digital Image and Remote Sensing Image

Authors: Riki Mukhaiyar

Abstract:

The integration between technology of remote sensing, information from the data of digital image, and modeling technology for the simulation of water quality will provide easiness during the observation on the quality of water changes on the river surface. For example, Ciliwung River which is contaminated with non-point source pollutant from household wastes, particularly on its downstream. This fact informed that the quality of water in this river is getting worse. The land use for settlements and housing ranges between 62.84% - 81.26% on the downstream of Ciliwung River, give a significant picture in seeing factors that affected the water quality of Ciliwung River.

Keywords: Digital Image, Digitize, Landuse, Non-Point SourcePollutant, Qual2e Simulation

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7662 Unequal Error Protection of Facial Features for Personal ID Images Coding

Authors: T. Hirner, J. Polec

Abstract:

This paper presents an approach for an unequal error protection of facial features of personal ID images coding. We consider unequal error protection (UEP) strategies for the efficient progressive transmission of embedded image codes over noisy channels. This new method is based on the progressive image compression embedded zerotree wavelet (EZW) algorithm and UEP technique with defined region of interest (ROI). In this case is ROI equal facial features within personal ID image. ROI technique is important in applications with different parts of importance. In ROI coding, a chosen ROI is encoded with higher quality than the background (BG). Unequal error protection of image is provided by different coding techniques and encoding LL band separately. In our proposed method, image is divided into two parts (ROI, BG) that consist of more important bytes (MIB) and less important bytes (LIB). The proposed unequal error protection of image transmission has shown to be more appropriate to low bit rate applications, producing better quality output for ROI of the compresses image. The experimental results verify effectiveness of the design. The results of our method demonstrate the comparison of the UEP of image transmission with defined ROI with facial features and the equal error protection (EEP) over additive white gaussian noise (AWGN) channel.

Keywords: Embedded zerotree wavelet (EZW), equal error protection (EEP), facial features, personal ID images, region of interest (ROI), unequal error protection (UEP)

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7661 Generation of Photo-Mosaic Images through Block Matching and Color Adjustment

Authors: Hae-Yeoun Lee

Abstract:

Mosaic refers to a technique that makes image by gathering lots of small materials in various colors. This paper presents an automatic algorithm that makes the photo-mosaic image using photos. The algorithm is composed of 4 steps: partition and feature extraction, block matching, redundancy removal and color adjustment. The input image is partitioned in the small block to extract feature. Each block is matched to find similar photo in database by comparing similarity with Euclidean difference between blocks. The intensity of the block is adjusted to enhance the similarity of image by replacing the value of light and darkness with that of relevant block. Further, the quality of image is improved by minimizing the redundancy of tiles in the adjacent blocks. Experimental results support that the proposed algorithm is excellent in quantitative analysis and qualitative analysis.

Keywords: Photo-mosaic, Euclidean distance, Block matching, Intensity adjustment.

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7660 Layout Design Optimization of Spars under Multiple Load Cases of the High-Aspect-Ratio Wing

Authors: Yu Li, Jingwu He, Yuexi Xiong

Abstract:

The spar layout will affect the wing’s stiffness characteristics, and irrational spar arrangement will reduce the overall bending and twisting resistance capacity of the wing. In this paper, the active structural stiffness design theory is used to match the stiffness-center axis position and load-cases under the corresponding multiple flight conditions, in order to achieve better stiffness properties of the wing. The combination of active stiffness method and principle of stiffness distribution is proved to be reasonable supplying an initial reference for wing designing. The optimized layout of spars is eventually obtained, and the high-aspect-ratio wing will have better stiffness characteristics.

Keywords: Active structural stiffness design theory, high-aspect-ratio wing, flight load cases, layout of spars.

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