Search results for: infrared image
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3747

Search results for: infrared image

3567 Scientific Investigation for an Ancient Egyptian Polychrome Wooden Stele

Authors: Ahmed Abdrabou, Medhat Abdalla

Abstract:

The studied stele dates back to Third Intermediate Period (1075-664) B.C in an ancient Egypt. It is made of wood and covered with painted gesso layers. This study aims to use a combination of multi spectral imaging {visible, infrared (IR), Visible-induced infrared luminescence (VIL), Visible-induced ultraviolet luminescence (UVL) and ultraviolet reflected (UVR)}, along with portable x-ray fluorescence in order to map and identify the pigments as well as to provide a deeper understanding of the painting techniques. Moreover; the authors were significantly interested in the identification of wood species. Multispectral imaging acquired in 3 spectral bands, ultraviolet (360-400 nm), visible (400-780 nm) and infrared (780-1100 nm) using (UV Ultraviolet-induced luminescence (UVL), UV Reflected (UVR), Visible (VIS), Visible-induced infrared luminescence (VIL) and Infrared photography. False color images are made by digitally editing the VIS with IR or UV images using Adobe Photoshop. Optical Microscopy (OM), potable X-ray fluorescence spectroscopy (p-XRF) and Fourier Transform Infrared Spectroscopy (FTIR) were used in this study. Mapping and imaging techniques provided useful information about the spatial distribution of pigments, in particular visible-induced luminescence (VIL) which allowed the spatial distribution of Egyptian blue pigment to be mapped and every region containing Egyptian blue, even down to single crystals in some instances, is clearly visible as a bright white area; however complete characterization of the pigments requires the use of p. XRF spectroscopy. Based on the elemental analysis found by P.XRF, we conclude that the artists used mixtures of the basic mineral pigments to achieve a wider palette of hues. Identification of wood species Microscopic identification indicated that the wood used was Sycamore Fig (Ficus sycomorus L.) which is recorded as being native to Egypt and was used to make wooden artifacts since at least the Fifth Dynasty.

Keywords: polychrome wooden stele, multispectral imaging, IR luminescence, Wood identification, Sycamore Fig, p-XRF

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3566 Temperature Coefficients of the Refractive Index for Ge Film

Authors: Lingmao Xu, Hui Zhou

Abstract:

Ge film is widely used in infrared optical systems. Because of the special requirements of space application, it is usually used in low temperature. The refractive index of Ge film is always changed with the temperature which has a great effect on the manufacture of high precision infrared optical film. Specimens of Ge single film were deposited at ZnSe substrates by EB-PVD method. During temperature range 80K ~ 300K, the transmittance of Ge single film within 2 ~ 15 μm were measured every 20K by PerkinElmer FTIR cryogenic testing system. By the full spectrum inversion method fitting, the relationship between refractive index and wavelength within 2 ~ 12μm at different temperatures was received. It can be seen the relationship consistent with the formula Cauchy, which can be fitted. Then the relationship between refractive index of the Ge film and temperature/wavelength was obtained by fitting method based on formula Cauchy. Finally, the designed value obtained by the formula and the measured spectrum were compared to verify the accuracy of the formula.

Keywords: infrared optical film, low temperature, thermal refractive coefficient, Ge film

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3565 Real-Time Classification of Hemodynamic Response by Functional Near-Infrared Spectroscopy Using an Adaptive Estimation of General Linear Model Coefficients

Authors: Sahar Jahani, Meryem Ayse Yucel, David Boas, Seyed Kamaledin Setarehdan

Abstract:

Near-infrared spectroscopy allows monitoring of oxy- and deoxy-hemoglobin concentration changes associated with hemodynamic response function (HRF). HRF is usually affected by natural physiological hemodynamic (systemic interferences) which occur in all body tissues including brain tissue. This makes HRF extraction a very challenging task. In this study, we used Kalman filter based on a general linear model (GLM) of brain activity to define the proportion of systemic interference in the brain hemodynamic. The performance of the proposed algorithm is evaluated in terms of the peak to peak error (Ep), mean square error (MSE), and Pearson’s correlation coefficient (R2) criteria between the estimated and the simulated hemodynamic responses. This technique also has the ability of real time estimation of single trial functional activations as it was applied to classify finger tapping versus resting state. The average real-time classification accuracy of 74% over 11 subjects demonstrates the feasibility of developing an effective functional near infrared spectroscopy for brain computer interface purposes (fNIRS-BCI).

Keywords: hemodynamic response function, functional near-infrared spectroscopy, adaptive filter, Kalman filter

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3564 Content-Based Image Retrieval Using HSV Color Space Features

Authors: Hamed Qazanfari, Hamid Hassanpour, Kazem Qazanfari

Abstract:

In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.

Keywords: content-based image retrieval, color difference histogram, efficient features selection, entropy, correlation

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3563 Self –Engineering Strategy of Six Dimensional Inter-Subcultural Mental Images

Authors: Mostafa Jafari

Abstract:

How the people continually create and recreate the six dimensional inter- sub-cultural relationships from the strategic point of view? Can they engineer and direct it toward creating a set of peaceful subcultures? This paper answers to these questions. Our mental images shape the quantity and quality of our relationships. The six dimensions of mental images are: my mental image about myself, your mental image about yourself, my mental image about you, your mental image about me, my imagination about your image about me and your imagination about my mental image about you. Strategic engineering is dynamically shaping these images and imaginations.Methodology: This survey, which is based on object and the relation between the variables, is explanatory, correlative and quantitative. The target community members are 90 educated people from universities. The data has been collected through questionnaire and interview and has been analyzed by descriptive statistical techniques and qualitative method. Results: Our findings show that engineering and deliberatly managing the process of inter- sub-cultural transactions in the national and global level can enable us to continually reform a peaceful set of learner sub-culturals toward recreate a peaceful unit global Home.

Keywords: strategic engineering, mental image, six dimensional mental images strategy , cultural literacy, radar technique

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3562 Rapid, Automated Characterization of Microplastics Using Laser Direct Infrared Imaging and Spectroscopy

Authors: Andreas Kerstan, Darren Robey, Wesam Alvan, David Troiani

Abstract:

Over the last 3.5 years, Quantum Cascade Lasers (QCL) technology has become increasingly important in infrared (IR) microscopy. The advantages over fourier transform infrared (FTIR) are that large areas of a few square centimeters can be measured in minutes and that the light intensive QCL makes it possible to obtain spectra with excellent S/N, even with just one scan. A firmly established solution of the laser direct infrared imaging (LDIR) 8700 is the analysis of microplastics. The presence of microplastics in the environment, drinking water, and food chains is gaining significant public interest. To study their presence, rapid and reliable characterization of microplastic particles is essential. Significant technical hurdles in microplastic analysis stem from the sheer number of particles to be analyzed in each sample. Total particle counts of several thousand are common in environmental samples, while well-treated bottled drinking water may contain relatively few. While visual microscopy has been used extensively, it is prone to operator error and bias and is limited to particles larger than 300 µm. As a result, vibrational spectroscopic techniques such as Raman and FTIR microscopy have become more popular, however, they are time-consuming. There is a demand for rapid and highly automated techniques to measure particle count size and provide high-quality polymer identification. Analysis directly on the filter that often forms the last stage in sample preparation is highly desirable as, by removing a sample preparation step it can both improve laboratory efficiency and decrease opportunities for error. Recent advances in infrared micro-spectroscopy combining a QCL with scanning optics have created a new paradigm, LDIR. It offers improved speed of analysis as well as high levels of automation. Its mode of operation, however, requires an IR reflective background, and this has, to date, limited the ability to perform direct “on-filter” analysis. This study explores the potential to combine the filter with an infrared reflective surface filter. By combining an IR reflective material or coating on a filter membrane with advanced image analysis and detection algorithms, it is demonstrated that such filters can indeed be used in this way. Vibrational spectroscopic techniques play a vital role in the investigation and understanding of microplastics in the environment and food chain. While vibrational spectroscopy is widely deployed, improvements and novel innovations in these techniques that can increase the speed of analysis and ease of use can provide pathways to higher testing rates and, hence, improved understanding of the impacts of microplastics in the environment. Due to its capability to measure large areas in minutes, its speed, degree of automation and excellent S/N, the LDIR could also implemented for various other samples like food adulteration, coatings, laminates, fabrics, textiles and tissues. This presentation will highlight a few of them and focus on the benefits of the LDIR vs classical techniques.

Keywords: QCL, automation, microplastics, tissues, infrared, speed

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3561 Nostalgic Tourism in Macau: The Bidirectional Causal Relationship between Destination Image and Experiential Value

Authors: Aliana Leong, T. C. Huan

Abstract:

The purpose of Nostalgic themed tourism product is becoming popular in many countries. This study intends to investigate the role of nostalgia in destination image, experiential value and their effect on subsequent behavioral intention. The survey used stratified sampling method to include respondents from all the nearby Asian regions. The sampling is based on the data of inbound tourists provided by the Statistics and Census Service (DSEC) of government of Macau. The questionnaire consisted of five sections of 5 point Likert scale questions: (1) nostalgia, (2) destination image both before and after experience, (3) expected value, (4) experiential value, and (5) future visit intention. Data was analysed with structural equation modelling. The result indicates that nostalgia plays an important part in forming destination image and experiential value before individual had a chance to experience the destination. The destination image and experiential value share a bidirectional causal relationship that eventually contributes to future visit intention. The study also discovered that while experiential value is more effective in generating destination image, the later contribute more to future visit intention. The research design measures destination image and experiential value before and after respondents had experience the destination. The distinction between destination image and expected/experiential value can be examined because the longitudinal design of research method. It also allows this study to observe how nostalgia translates to future visit intention.

Keywords: nostalgia, destination image, experiential value, future visit intention

Procedia PDF Downloads 365
3560 Enhanced Visual Sharing Method for Medical Image Security

Authors: Kalaivani Pachiappan, Sabari Annaji, Nithya Jayakumar

Abstract:

In recent years, Information security has emerged as foremost challenges in many fields. Especially in medical information systems security is a major issue, in handling reports such as patients’ diagnosis and medical images. These sensitive data require confidentiality for transmission purposes. Image sharing is a secure and fault-tolerant method for protecting digital images, which can use the cryptography techniques to reduce the information loss. In this paper, visual sharing method is proposed which embeds the patient’s details into a medical image. Then the medical image can be divided into numerous shared images and protected by various users. The original patient details and medical image can be retrieved by gathering the shared images.

Keywords: information security, medical images, cryptography, visual sharing

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3559 An Image Segmentation Algorithm for Gradient Target Based on Mean-Shift and Dictionary Learning

Authors: Yanwen Li, Shuguo Xie

Abstract:

In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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3558 Improvement of Brain Tumors Detection Using Markers and Boundaries Transform

Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

Abstract:

This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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3557 Assessment of Planet Image for Land Cover Mapping Using Soft and Hard Classifiers

Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

Abstract:

Planet image is a new data source from planet lab. This research is concerned with the assessment of Planet image for land cover mapping. Two pixel based classifiers and one subpixel based classifier were compared. Firstly, rectification of Planet image was performed. Secondly, a comparison between minimum distance, maximum likelihood and neural network classifications for classification of Planet image was performed. Thirdly, the overall accuracy of classification and kappa coefficient were calculated. Results indicate that neural network classification is best followed by maximum likelihood classifier then minimum distance classification for land cover mapping.

Keywords: planet image, land cover mapping, rectification, neural network classification, multilayer perceptron, soft classifiers, hard classifiers

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3556 Survivability of Maneuvering Aircraft against Air to Air Infrared Missile

Authors: Ji-Yeul Bae, Hyung Mo Bae, Jihyuk Kim, Hyung Hee Cho

Abstract:

An air to air infrared missile poses a significant threat to the survivability of an aircraft due to an advanced sensitivity of sensor and maneuverability of the missile. Therefore, recent military aircraft is equipped with MAW (Missile Approach Warning) to take an evasive maneuver and to deploy countermeasures like chaff and flare. In this research, an effect of MAW sensitivity and resulting evasive maneuver on the survivability of the fighter aircraft is studied. A single engine fighter jet with Mach 0.9 flying at an altitude of 5 km is modeled in the research and infrared signature of the aircraft is calculated by numerical simulation. The survivability is assessed in terms of lethal range. The MAW sensitivity and maneuverability of an aircraft is used as variables. The result showed that improvement in survivability mainly achieved when the missile approach from the side of the aircraft. And maximum 30% increase in survivability of the aircraft is achieved when existence of the missile is noticed at 7 km distance. As a conclusion, sensitivity of the MAW seems to be more important factor than the maneuverability of the aircraft in terms of the survivability.

Keywords: air to air missile, missile approach warning, lethal range, survivability

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3555 Efficient Feature Fusion for Noise Iris in Unconstrained Environment

Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: image fusion, iris recognition, local binary pattern, wavelet

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3554 Effective Corporate Image Management as a Strategy for Enhancing Profitability

Authors: Shola Haruna Adeosun, Ajoke F. Adebiyi

Abstract:

Business organizations in Nigeria have failed to realize the role of a good corporate image policy in business dealings. This is probably because they do not understand the concept of corporate image and the necessary tools for promoting it. Corporate image goes beyond attractive products or rendering quality services, advertising and paying good salary. It pervades every aspect of business concern, from the least worker’s personality to the dealings within the organization and with the large society. In the face of the societal dynamics, especially in the business world, brought by technology, companies are faced with stiff competition that maintaining a competitive edge requires aggressive strategies. One of such strategies in effective corporate image management is promotion. This study investigates the strategies that could be deployed in order to build and promote the effective corporate image, as well as enhance profit margins of an organization, using Phinomar Nigeria Limited, Ngwo as case study. The study reveals that Phinomar Nigeria Limited has a laid down corporate image policy but not effectively managed; and that, strategies deployed to promote corporate image are limited; while responses to Phinomar products are fairly high. It, therefore, suggests profitable products but requires periodical improvement in the employee's welfare and work environment; as well as, the need to increase the scope of Phinomar’s social responsibility.

Keywords: corporate image, effective, enhancing, management, profitability, strategy

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3553 Detection of Image Blur and Its Restoration for Image Enhancement

Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

Abstract:

Image restoration in the process of communication is one of the emerging fields in the image processing. The motion analysis processing is the simplest case to detect motion in an image. Applications of motion analysis widely spread in many areas such as surveillance, remote sensing, film industry, navigation of autonomous vehicles, etc. The scene may contain multiple moving objects, by using motion analysis techniques the blur caused by the movement of the objects can be enhanced by filling-in occluded regions and reconstruction of transparent objects, and it also removes the motion blurring. This paper presents the design and comparison of various motion detection and enhancement filters. Median filter, Linear image deconvolution, Inverse filter, Pseudoinverse filter, Wiener filter, Lucy Richardson filter and Blind deconvolution filters are used to remove the blur. In this work, we have considered different types and different amount of blur for the analysis. Mean Square Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the performance of the filters. The designed system has been implemented in Matlab software and tested for synthetic and real-time images.

Keywords: image enhancement, motion analysis, motion detection, motion estimation

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3552 Non-Invasive Imaging of Tissue Using Near Infrared Radiations

Authors: Ashwani Kumar Aggarwal

Abstract:

NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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3551 Optimization Query Image Using Search Relevance Re-Ranking Process

Authors: T. G. Asmitha Chandini

Abstract:

Web-based image search re-ranking, as an successful method to get better the results. In a query keyword, the first stair is store the images is first retrieve based on the text-based information. The user to select a query keywordimage, by using this query keyword other images are re-ranked based on their visual properties with images.Now a day to day, people projected to match images in a semantic space which is used attributes or reference classes closely related to the basis of semantic image. though, understanding a worldwide visual semantic space to demonstrate highly different images from the web is difficult and inefficient. The re-ranking images, which automatically offline part learns dissimilar semantic spaces for different query keywords. The features of images are projected into their related semantic spaces to get particular images. At the online stage, images are re-ranked by compare their semantic signatures obtained the semantic précised by the query keyword image. The query-specific semantic signatures extensively improve both the proper and efficiency of image re-ranking.

Keywords: Query, keyword, image, re-ranking, semantic, signature

Procedia PDF Downloads 526
3550 Land Cover Classification Using Sentinel-2 Image Data and Random Forest Algorithm

Authors: Thanh Noi Phan, Martin Kappas, Jan Degener

Abstract:

The currently launched Sentinel 2 (S2) satellite (June, 2015) bring a great potential and opportunities for land use/cover map applications, due to its fine spatial resolution multispectral as well as high temporal resolutions. So far, there are handful studies using S2 real data for land cover classification. Especially in northern Vietnam, to our best knowledge, there exist no studies using S2 data for land cover map application. The aim of this study is to provide the preliminary result of land cover classification using Sentinel -2 data with a rising state – of – art classifier, Random Forest. A case study with heterogeneous land use/cover in the eastern of Hanoi Capital – Vietnam was chosen for this study. All 10 spectral bands of 10 and 20 m pixel size of S2 images were used, the 10 m bands were resampled to 20 m. Among several classified algorithms, supervised Random Forest classifier (RF) was applied because it was reported as one of the most accuracy methods of satellite image classification. The results showed that the red-edge and shortwave infrared (SWIR) bands play an important role in land cover classified results. A very high overall accuracy above 90% of classification results was achieved.

Keywords: classify algorithm, classification, land cover, random forest, sentinel 2, Vietnam

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3549 Radial Distortion Correction Based on the Concept of Verifying the Planarity of a Specimen

Authors: Shih-Heng Tung, Ming-Hsiang Shih, Wen-Pei Sung

Abstract:

Because of the rapid development of digital camera and computer, digital image correlation method has drawn lots of attention recently and has been applied to a variety of fields. However, the image distortion is inevitable when the image is captured through a lens. This image distortion problem can result in an innegligible error while using digital image correlation method. There are already many different ways to correct the image distortion, and most of them require specific image patterns or precise control points. A new distortion correction method is proposed in this study. The proposed method is based on the fact that a flat surface should keep flat when it is measured using three-dimensional (3D) digital image measurement technique. Lens distortion can be divided into radial distortion, decentering distortion and thin prism distortion. Because radial distortion has a more noticeable influence than the other types of distortions, this method deals only with radial distortion. The simplified 3D digital image measurement technique is adopted to measure the surface coordinates of a flat specimen. Then the gradient method is applied to find the best correction parameters. A few experiments are carried out in this study to verify the correctness of this method. The results show that this method can achieve a good accuracy and it is suitable for both large and small distortion conditions. The most important advantage is that it requires neither mark with specific pattern nor precise control points.

Keywords: 3D DIC, radial distortion, distortion correction, planarity

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3548 The Use of Image Processing Responses Tools Applied to Analysing Bouguer Gravity Anomaly Map (Tangier-Tetuan's Area-Morocco)

Authors: Saad Bakkali

Abstract:

Image processing is a powerful tool for the enhancement of edges in images used in the interpretation of geophysical potential field data. Arial and terrestrial gravimetric surveys were carried out in the region of Tangier-Tetuan. From the observed and measured data of gravity Bouguer gravity anomalies map was prepared. This paper reports the results and interpretations of the transformed maps of Bouguer gravity anomaly of the Tangier-Tetuan area using image processing. Filtering analysis based on classical image process was applied. Operator image process like logarithmic and gamma correction are used. This paper also present the results obtained from this image processing analysis of the enhancement edges of the Bouguer gravity anomaly map of the Tangier-Tetuan zone.

Keywords: bouguer, tangier, filtering, gamma correction, logarithmic enhancement edges

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3547 Body Image Impact on Quality of Life and Adolescents’ Binge Eating: The Indirect Role of Body Image Coping Strategies

Authors: Dora Bianchi, Anthony Schinelli, Laura Maria Fatta, Antonia Lonigro, Fabio Lucidi, Fiorenzo Laghi

Abstract:

Purpose: The role of body image in adolescent binge eating is widely confirmed, albeit the various facets of this relationship are still mostly unexplored. Within the multidimensional body image framework, this study hypothesized the indirect effects of three body image coping strategies (positive rational acceptance, appearance fixing, avoidance) in the expected relationship between the perceived impact of body image on individuals’ quality of life and binge eating symptoms. Methods: Participants were 715 adolescents aged 15-21 years (49.1% girls) recruited in Italian schools. An anonymous self-report online survey was administered. A multiple mediation model was tested. Results: A more positive perceived impact of body image on quality of life was a negative predictor of adolescents’ binge eating, controlling for individual levels of body satisfaction. Three indirect effects were found in this relationship: on one hand, the positive body image impact reduced binge eating via increasing positive rational acceptance (M1), and via reducing avoidance (M2); on the contrary, the positive body image impact also enhanced binge eating via increasing appearance fixing (M3). Conclusions: The body image impact on quality of life can be alternatively protective—when adaptive coping is solicited, and maladaptive strategies are reduced—or a risk factor, which may increase binge eating by soliciting appearance fixing.

Keywords: binge eating, body image satisfaction, quality of life, coping strategies, adolescents

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3546 Landsat 8-TIRS NEΔT at Kīlauea Volcano and the Active East Rift Zone, Hawaii

Authors: Flora Paganelli

Abstract:

The radiometric performance of remotely sensed images is important for volcanic monitoring. The Thermal Infrared Sensor (TIRS) on-board Landsat 8 was designed with specific requirements in regard to the noise-equivalent change in temperature (NEΔT) at ≤ 0.4 K at 300 K for the two thermal infrared bands B10 and B11. This study investigated the on-orbit NEΔT of the TIRS two bands from a scene-based method using clear-sky images over the volcanic activity of Kīlauea Volcano and the active East Rift Zone (Hawaii), in order to optimize the use of TIRS data. Results showed that the NEΔTs of the two bands exceeded the design specification by an order of magnitude at 300 K. Both separate bands and split window algorithm were examined to estimate the effect of NEΔT on the land surface temperature (LST) retrieval, and NEΔT contribution to the final LST error. These results were also useful in the current efforts to assess the requirements for volcanology research campaign using the Hyperspectral Infrared Imager (HyspIRI) whose airborne prototype MODIS/ASTER instruments is plan to be flown by NASA as a single campaign to the Hawaiian Islands in support of volcanology and coastal area monitoring in 2016.

Keywords: landsat 8, radiometric performance, thermal infrared sensor (TIRS), volcanology

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3545 A New Categorization of Image Quality Metrics Based on a Model of Human Quality Perception

Authors: Maria Grazia Albanesi, Riccardo Amadeo

Abstract:

This study presents a new model of the human image quality assessment process: the aim is to highlight the foundations of the image quality metrics proposed in literature, by identifying the cognitive/physiological or mathematical principles of their development and the relation with the actual human quality assessment process. The model allows to create a novel categorization of objective and subjective image quality metrics. Our work includes an overview of the most used or effective objective metrics in literature, and, for each of them, we underline its main characteristics, with reference to the rationale of the proposed model and categorization. From the results of this operation, we underline a problem that affects all the presented metrics: the fact that many aspects of human biases are not taken in account at all. We then propose a possible methodology to address this issue.

Keywords: eye-tracking, image quality assessment metric, MOS, quality of user experience, visual perception

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3544 Error Analysis of Wavelet-Based Image Steganograhy Scheme

Authors: Geeta Kasana, Kulbir Singh, Satvinder Singh

Abstract:

In this paper, a steganographic scheme for digital images using Integer Wavelet Transform (IWT) is proposed. The cover image is decomposed into wavelet sub bands using IWT. Each of the subband is divided into blocks of equal size and secret data is embedded into the largest and smallest pixel values of each block of the subband. Visual quality of stego images is acceptable as PSNR between cover image and stego is above 40 dB, imperceptibility is maintained. Experimental results show better tradeoff between capacity and visual perceptivity compared to the existing algorithms. Maximum possible error analysis is evaluated for each of the wavelet subbands of an image.

Keywords: DWT, IWT, MSE, PSNR

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3543 Brand Management Model in Professional Football League

Authors: Vajiheh Javani

Abstract:

The study aims to examine brand image in Iran's professional Football League (2014-2015). The study was descriptive survey one. A sample of Iranian professional football league fans (N=911) responded four items questionnaire. A structural equation model (SEM) test with maximum likelihood estimation was performed to test the relationships among the research variables. The analyses of data showed three dimensions of brand image influenced on fan’s brand loyalty of which the attitude was the most important. Benefits and attributes were placed in the second and third rank respectively. According to results, brand image plays a pivotal role between Iranian fans brand loyalty. Create an attractive and desirable brand image in the fans mind increases brand loyalty. Moreover due to, revenue and profits increase through ticket sales and products of club and also attract more sponsors.

Keywords: brand management, sport industry, brand image, fans

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3542 Implementation and Comparative Analysis of PET and CT Image Fusion Algorithms

Authors: S. Guruprasad, M. Z. Kurian, H. N. Suma

Abstract:

Medical imaging modalities are becoming life saving components. These modalities are very much essential to doctors for proper diagnosis, treatment planning and follow up. Some modalities provide anatomical information such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), X-rays and some provides only functional information such as Positron Emission Tomography (PET). Therefore, single modality image does not give complete information. This paper presents the fusion of structural information in CT and functional information present in PET image. This fused image is very much essential in detecting the stages and location of abnormalities and in particular very much needed in oncology for improved diagnosis and treatment. We have implemented and compared image fusion techniques like pyramid, wavelet, and principal components fusion methods along with hybrid method of DWT and PCA. The performances of the algorithms are evaluated quantitatively and qualitatively. The system is implemented and tested by using MATLAB software. Based on the MSE, PSNR and ENTROPY analysis, PCA and DWT-PCA methods showed best results over all experiments.

Keywords: image fusion, pyramid, wavelets, principal component analysis

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3541 Deep Learning based Image Classifiers for Detection of CSSVD in Cacao Plants

Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

Abstract:

The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

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3540 A Structural Model to Examine Hotel Image and Overall Satisfaction on Future Behavior of Customers

Authors: Nimit Soonsan

Abstract:

Hotel image is a key business issue in today’s hotel market and has been increasingly been recognized as a valuable and inimitable source of competitive advantage by many hotel. The current study attempted to develop and test a relationship of hotel image, overall satisfaction, and future behavior. Based on the above concepts, this paper hypothesizes the correlations among four constructs, namely, hotel image and overall satisfaction as antecedents of future behavior that positive word-of-mouth and intention to revisit. This study surveyed for a sample of 244 international customers staying budget hotel in Phuket, Thailand and using a structural equation modeling identified relationship between hotel image, overall satisfaction and future behavior. The major finding of structural equation modeling indicates that hotel image directly affects overall satisfaction and indirectly affects future behavior that positive word-of-mouth and intention to revisit. In addition, overall satisfaction had significant influence on future behavior that positive word-of-mouth and intention to revisit, and the mediating role of overall satisfaction is also confirmed in this study. Managerial implications are provided, limitations noted, and future research directions suggested.

Keywords: hotel image, satisfaction, word-of-mouth, revisit

Procedia PDF Downloads 197
3539 An Improvement of Multi-Label Image Classification Method Based on Histogram of Oriented Gradient

Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

Abstract:

Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

Procedia PDF Downloads 347
3538 City Image of Rio De Janeiro as the Host City of 2016 Olympic Games

Authors: Luciana Brandao Ferreira, Janaina de Moura Engracia Giraldi, Fabiana Gondim Mariutti, Marina Toledo de Arruda Lourencao

Abstract:

Developing countries, such as BRICS (Brazil, Russia, India, China and South Africa) are hosting sports mega-events to promote socio-economic development and image enhancement. Thus, this paper aims to verify the image of Rio de Janeiro, in Brazil, as the host city of 2016 Olympic Games, considering the main cognitive and affective image dimensions. The research design uses exploratory factorial analysis to find the most important factors highlighted in the city image dimensions. The data were collected by structured questionnaires with an international respondents sample (n=274) with high international travel experience. The results show that Rio’s image as a sport mega-event host city has two main factors in each dimension: Cognitive ('General Infrastructure'; 'Services and Attractions') and Affective ('Positive Feelings'; 'Negative Feelings'). The most important factor related to cognitive dimension was 'Services and Attractions' which is more related to tourism activities. In the affective dimension 'Positive Feelings' was the most important factor, which means a good result considering that is a city in an emerging country with many unmet social demands.

Keywords: Rio de Janeiro, 2016 olympic games, host city image, cognitive image dimension, affective image dimension

Procedia PDF Downloads 123