1,275 research outputs found

    Map online system using internet-based image catalogue

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    Digital maps carry along its geodata information such as coordinate that is important in one particular topographic and thematic map. These geodatas are meaningful especially in military field. Since the maps carry along this information, its makes the size of the images is too big. The bigger size, the bigger storage is required to allocate the image file. It also can cause longer loading time. These conditions make it did not suitable to be applied in image catalogue approach via internet environment. With compression techniques, the image size can be reduced and the quality of the image is still guaranteed without much changes. This report is paying attention to one of the image compression technique using wavelet technology. Wavelet technology is much batter than any other image compression technique nowadays. As a result, the compressed images applied to a system called Map Online that used Internet-based Image Catalogue approach. This system allowed user to buy map online. User also can download the maps that had been bought besides using the searching the map. Map searching is based on several meaningful keywords. As a result, this system is expected to be used by Jabatan Ukur dan Pemetaan Malaysia (JUPEM) in order to make the organization vision is implemented

    An Investigation into the Effects of Image Resolution on a Facial-Image-Based Personal Authentication System

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    The issues associated with image resolution in automated authentication or identification systems has become one of the important challenges for researchers' in biometrics. The aim of this thesis is to investigate the effect of variable resolutions on the performance of a Facial-Image-Based Person Authentication System. Image resolution may vary significantly especially in uncontrolled acquisition environments or when sensing from a distance and so on. The detail available in the data thus reduces which may deteriorate the performance of such system. In this project we investigated the impact on system accuracy when image resolution is gradually reduced by a given factor. As a remedy, we investigated different methods for increasing image resolution prior to using those images for authentication and compared the relative gains in accuracy. The main procedure of the face image authentication system based on comparing landmarks of the face remains the same. In this study, we found that several issues related to image resolutions might have an impact on the recognition rate performance such as facial expressions, image background, and others. The influence of image resolution on the recognition rate increases roughly with the increasing resolution at a specific degree, high-image resolution would not be good for recognition rate always; reducing high image resolution makes it easier to achieve high face recognition rates

    Fitting and tracking of a scene model in very low bit rate video coding

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    Signal and data processing for machine olfaction and chemical sensing: A review

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    Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing

    Intelligent Biosignal Processing in Wearable and Implantable Sensors

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    This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brain–machine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine

    The manufacturing and the application of polycrystalline diamond tools – A comprehensive review

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    Advanced materials such as titanium alloys and metal matrix composites are extensively used in the aerospace industry and biomedical engineering. They are difficult to machine because of the severe abrasion and high temperature at the tool/chip and tool/workpiece interfaces which cause severe tool wear and premature tool rejection. Compared with conventional cutting tools, polycrystalline diamond (PCD) tools are promising in machining refractory metals and hard-to-machine materials because of the outstanding mechanical properties of PCD. This paper reviewed the manufacturing and application of PCD cutting tools. The researches on manufacturing process of PCD tools and the application in cutting hard-to-machine materials were analysed, and the results and findings were comprehensively discussed. Two most widely used refining methods including abrasive grinding and electrical discharge grinding (EDG) as well as the defects caused by the processes were presented. The wear process of PCD tools in different industrial cutting methods and the wear mechanism of different PCD materials were explained in both micro-scale and macro-scale. Research directions and the trend of the application of PCD cutting tools were introduced

    An overview of signal processing issues in chemical sensing

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    International audienceThis tutorial paper aims at summarizing some problems, ranging from analytical chemistry to novel chemical sensors, that can be addressed with classical or advanced methods of signal and image processing. We gather them under the denomination of "chemical sensing". It is meant to introduce the special session "Signal Processing for Chemical Sensing" with a large overview of issues which have been and remain to be addressed in this application domain, including chemical analysis leading to PARAFAC/tensor methods, hyper spectral imaging, ion-sensitive sensors, artificial nose, chromatography, mass spectrometry, etc. For enlarging and illustrating the points of view of this tutorial, the invited papers of the session consider other applications (NMR, Raman spectroscopy, recognition of explosive compounds, etc.) addressed by various methods, e.g. source separation, Bayesian, and exploiting typical chemical signal priors like positivity, linearity, unit-concentration or sparsity

    2D Face Recognition System Based on Selected Gabor Filters and Linear Discriminant Analysis LDA

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    We present a new approach for face recognition system. The method is based on 2D face image features using subset of non-correlated and Orthogonal Gabor Filters instead of using the whole Gabor Filter Bank, then compressing the output feature vector using Linear Discriminant Analysis (LDA). The face image has been enhanced using multi stage image processing technique to normalize it and compensate for illumination variation. Experimental results show that the proposed system is effective for both dimension reduction and good recognition performance when compared to the complete Gabor filter bank. The system has been tested using CASIA, ORL and Cropped YaleB 2D face images Databases and achieved average recognition rate of 98.9 %

    A survey of the application of soft computing to investment and financial trading

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