Search results for: image narrative

Authors: R. Kiruthika, A. Kannan

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Steganography is the problem of hiding secret messages in 'innocent – looking' public communication so that the presence of the secret message cannot be detected. This paper introduces a steganographic security in terms of computational in-distinguishability from a channel of probability distributions on cover messages. This method first splits the cover image into two separate blocks using Douglas – Peucker algorithm. The text message and the image will be hided in the Least Significant Bit (LSB) of the cover image.

Keywords: steganography, lsb, embedding, Douglas-Peucker algorithm

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Authors: Bin Liu, Weijie Liu, Bin Sun, Yihui Luo

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In order to solve the problem of lower spatial resolution and block effect in the fusion method based on separable wavelet transform in the resulting fusion image, a new sampling mode based on multi-resolution analysis of two-channel non separable wavelet transform, whose dilation matrix is [1,1;1,-1], is presented and a multispectral image fusion method based on this kind of sampling mode is proposed. Filter banks related to this kind of wavelet are constructed, and multiresolution decomposition of the intensity of the MS and panchromatic image are performed in the sampled mode using the constructed filter bank. The low- and high-frequency coefficients are fused by different fusion rules. The experiment results show that this method has good visual effect. The fusion performance has been noted to outperform the IHS fusion method, as well as, the fusion methods based on DWT, IHS-DWT, IHS-Contourlet transform, and IHS-Curvelet transform in preserving both spectral quality and high spatial resolution information. Furthermore, when compared with the fusion method based on nonsubsampled two-channel non separable wavelet, the proposed method has been observed to have higher spatial resolution and good global spectral information.

Keywords: image fusion, two-channel sampled nonseparable wavelets, multispectral image, panchromatic image

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Authors: Ashis Pradhan, Mohan P. Pradhan

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Pattern Matching is useful for recognizing character in a digital image. OCR is one such technique which reads character from a digital image and recognizes them. Line segmentation is initially used for identifying character in an image and later refined by morphological operations like binarization, erosion, thinning, etc. The work discusses a recognition technique that defines a set of morphological operators based on its orientation in a character. These operators are further categorized into groups having similar shape but different orientation for efficient utilization of memory. Finally the characters are recognized in accordance with the occurrence of frequency in hierarchy of significant pattern of those morphological operators and by comparing them with the existing database of each character.

Keywords: binary image, morphological patterns, frequency count, priority, reduction data set and recognition

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Authors: Alison Brown

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Through stories, children make sense of their world, see themselves through the eyes of another, and process emotions and lived experiences in a non-threatening and indirect manner. Building on research around the use of narrative techniques with adults and families, this research looked directly at the use of narratives as a therapeutic technique with children in counseling. Based on individual therapy sessions with children over a six-year period, this work of collective case studies tells the story of a practice incorporating children’s narratives, of children’s experiences in writing and sharing their narratives, and of the clinical impact of the use of narratives with children. Not all stories were narratives of success or happiness. Children documented their fears and anger as well as their achievements and hope for the future. What emerged through this study was an awareness of recurring themes in the way children responded to the narrative process and in the benefits and limitations of story writing with children. Consistent with previous studies focusing on narrative work with adults and families, the use of narratives with children provided opportunities for healing, acceptance, developing greater understanding, externalizing, and re-authoring a preferred future. In terms of the children’s experiences in writing and sharing their narratives, consistent themes emerged again, with many children finding the experience cathartic and liberating, empowering and hopeful, but most importantly, an opportunity that allowed them to feel and understand that they were not alone. Whilst a small collection of case studies tells the stories of a limited number of children, it is hoped that this research provides both a model and inspiration for others to explore similar uses of narratives with children. As a greater number of children’s narratives are created, the potential to share and benefit from the many rich stories and experiences of other children becomes more of a reality. Across cultures, economic and social settings, rural and urban environments, and varying family structures, it is important that we hear the voices of our children – ‘In their own words’.

Keywords: narrative therapy children counselling, social, emotional, zone of proximal development, scaffolding

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Authors: Awad Mohamed Elkhadir, Rajab M. Ben Yousef

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Background/Aim: Radiological technologists are medical professionals who perform diagnostic imaging tests such as X-rays, magnetic resonance imaging (MRI) scans, and computer tomography (CT) scans. Despite the recognition of image interpretation by British radiologists, it is still considered a problem in the Arab world. This study evaluates the perceptions of radiologists in the Middle East concerning the plain image interpretation of adults by radiologic technologist specialists. Methods: This is a cross-sectional study that follows a quantitative approach. A close-ended questionnaire was distributed among 103 participants who were radiologists by profession from various hospitals in Saudi Arabia and Sudan. The gathered data was then analyzed through Statistical Package for Social Sciences (SPSS). Results: The results showed that 29% recognized the Radiologic Technologist Specialist (RTS) role of writing image reports, while 61% did not. A total of 38% of participants believed that RTS image interpretation would help diagnose unreported radiographs. 47% of the sample responded that the workload and stress on radiologists would reduce by allowing reporting for RTS, while 37% did not. Lastly, 43% believe that image interpretation by RTS can be introduced into the Middle East in the future. Conclusion: The study's findings reveal that the combination of image reporting and radiography improves the care of the patients. The study's outcomes also show that the burden of the medical practitioners reduces due to image reporting of the radiographers. Further researches need to be conducted in the Arab World to obtain and measure the associated factors of the desired criteria.

Keywords: Arab world, image interpretation, radiographer, radiologist, Saudi Arabia, Sudan

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Authors: Baljit Singh Khehra, Jagreeti Kaur

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In this paper, steganographic strategy is used to hide the text file inside an image. To increase the storage limit, predictive coding is utilized to implant information. In the proposed plan, one can exchange secure information by means of predictive coding methodology. The predictive coding produces high stego-image. The pixels are utilized to insert mystery information in it. The proposed information concealing plan is powerful as contrasted with the existing methodologies. By applying this strategy, a provision helps clients to productively conceal the information. Entropy, standard deviation, mean square error and peak signal noise ratio are the parameters used to evaluate the proposed methodology. The results of proposed approach are quite promising.

Keywords: cryptography, steganography, reversible image, predictive coding

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Authors: Awad Elkhadir, Rajab M. Ben Yousef

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Introduction: The production of high-quality medical images by radiology technologists is useful in diagnosing and treating various injuries and diseases. However, the factors affecting the role of radiology technologists in image interpretation in Sudan have not been investigated widely. Methods: Cross-sectional study has been employed by recruiting ten radiology college deans in Sudan. The questionnaire was distributed online, and obtained data were analyzed using Microsoft Excel and IBM-SPSS version 16.0 to generate descriptive statistics. Results: The study results have shown that half of the deans were doubtful about the readiness of Sudan to implement the role of radiology technologist specialist in image interpretation. The majority of them (60%) believed that this issue had been most strongly pushed by researchers over the past decade. The factors affecting the implementation of the radiology technologist specialist role in image interpretation included; education/training (100%), recognition (30%), technical issues (30%), people-related issues (20%), management changes (30%), government role (30%), costs (10%), and timings (20%). Conclusion: The study concluded that there is a need for a change in image interpretation by radiology technologists in Sudan.

Keywords: development, image interpretation, implementation, radiology technologist specialist, Sudan

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Authors: Kexin Tan

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The Silk Road is a concept idiosyncratic in nature. Western scholars co-created and conceptualized in its early days, transliterated into the countries along the Silk Road, redefined, reimagined, and reconfigured by the public in the second half of the twentieth century. Therefore, the image is not only a mirror of the discursive interactions between East and West but Self and Other. The travel narrative of Sven Hedin, through which the Silk Road was enriched in meanings and popularized, is the focus of this study. This article examines how the Silk Road was imagined in three key texts of Sven Hedin: The Silk Road, The Wandering Lake, and The Flight of “Big Horse”. Three recurring themes are extracted and analyzed: the Silk Road, the land of enigmas, the virgin land, and the reconnecting road. Ideas about ethnotypes and images drawn from theorists such as Joep Leerssen have been deployed in the analysis. This research tracks how the images were configured, concentrating on China’s ethnotypes, travel writing tropes, and the Silk Road discourse that preceded Sven Hedin. Hedin’s role in his expedition, his geopolitical viewpoints, and the commercial considerations of his books are also discussed in relation to the intellectual construct of the Silk Road. It is discovered that the images of the Silk Road and the discursive traditions behind it are mobile rather than static, inclusive than antithetical. The paradoxical characters of the Silk Road reveal the complexity of the socio-historical background of Hedin’s time, as well as the collision of discursive traditions and practical issues. While it is true that Hedin’s discursive construction of the Silk Road image embodies the bias of Self-West against Other-East, its characteristics such as fluidity and openness could probably offer a hint at its resurgence in the postcolonial era.

Keywords: the silk road, Sven Hedin, imagology, ethnotype, travelogue

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Authors: Peter U. Eze, P. Udaya, Robin J. Evans

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Data hiding can be achieved by Steganography or invisible digital watermarking. For digital watermarking, both accurate retrieval of the embedded watermark and the integrity of the cover image are important. Medical image security in Teleradiology is one of the applications where the embedded patient record needs to be extracted with accuracy as well as the medical image integrity verified. In this research paper, the Constant Correlation Spread Spectrum digital watermarking for medical image tamper detection and accurate embedded watermark retrieval is introduced. In the proposed method, a watermark bit from a patient record is spread in a medical image sub-block such that the correlation of all watermarked sub-blocks with a spreading code, W, would have a constant value, p. The constant correlation p, spreading code, W and the size of the sub-blocks constitute the secret key. Tamper detection is achieved by flagging any sub-block whose correlation value deviates by more than a small value, ℇ, from p. The major features of our new scheme include: (1) Improving watermark detection accuracy for high-pixel depth medical images by reducing the Bit Error Rate (BER) to Zero and (2) block-level tamper detection in a single computational process with simultaneous watermark detection, thereby increasing utility with the same computational cost.

Keywords: Constant Correlation, Medical Image, Spread Spectrum, Tamper Detection, Watermarking

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Authors: Bum-Soo Kim, Jin-Uk Kim

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In this paper, we design and implement a partial denoising boundary image matching system using indexing techniques. Converting boundary images to time-series makes it feasible to perform fast search using indexes even on a very large image database. Thus, using this converting method we develop a client-server system based on the previous partial denoising research in the GUI (graphical user interface) environment. The client first converts a query image given by a user to a time-series and sends denoising parameters and the tolerance with this time-series to the server. The server identifies similar images from the index by evaluating a range query, which is constructed using inputs given from the client, and sends the resulting images to the client. Experimental results show that our system provides much intuitive and accurate matching result.

Keywords: boundary image matching, indexing, partial denoising, time-series matching

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Heru Syah Putra, Aji Tri Pamungkas Nurcahyo, Chuang-Jan Chang

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MOIL-SDK method refers to the spatial angle that forms a view with a different perspective from the Fisheye image. Visual Odometry forms a trusted application for extending projects by tracking using image sequences. A real-time, precise, and persistent approach that is able to contribute to the work when taking datasets and generate ground truth as a reference for the estimates of each image using the FAST Algorithm method in finding Keypoints that are evaluated during the tracking process with the 5-point Algorithm with RANSAC, as well as produce accurate estimates the camera trajectory for each rotational, translational movement on the X, Y, and Z axes.

Keywords: MOIL-SDK, intel realsense T265, Fisheye image, monocular visual odometry

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Authors: Cara DiGirolamo

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In his 2017 Ph.D. thesis, script doctor David Baboulene presented a theory of fiction in which differences in the knowledge states between participants in a literary experience, including reader, author, and characters, create many story elements, among them suspense, expectations, subtext, theme, metaphor, and allegory. This theory can be adjusted and modeled by incorporating a formal pragmatic approach that understands narrative as a speech act with a conversational function. This approach requires both the Speaker and the Listener to be understood as participants in the discourse. It also uses theories of cooperativity and the QUD to identify the existence of implicit questions. This approach predicts that what an effective literary narrative must do: provide a conversational context early in the story so the reader can engage with the text as a conversational participant. In addition, this model incorporates schema theory. Schema theory is a cognitive model for learning and processing information about the world and transforming it into functional knowledge. Using this approach can extend the QUD model. Instead of describing conversation as a form of information gathering restricted to question-answer sets, the QUD can include knowledge modeling and understanding as a possible outcome of a conversation. With this model, Baboulene’s “Knowledge Gaps” can provide real insight into storytelling as a conversational move, and extend the QUD to be able to simply and effectively apply to a more diverse set of conversational interactions and also to narrative texts.

Keywords: literature, speech acts, QUD, literary theory

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Authors: Omaima N. Ahmad AL-Allaf

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Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

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Authors: Zinaida Shelkovnikova

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The language in science is changing and meets the demands of the society. We shall argue that in the varied modern world there are important reasons for the integration of narratives into scientific discourse. As far as nowadays scientists are faced with extremely prompt science development and progress; modern scientific society lives in the conditions of tough competition. The integration of narratives into scientific discourse is thus a good way to prompt scientific experience to different audiences and to express covert prestige of the discourse. Narratives also form the identity of the persuasive narrator. Using the narrative approach to the scientific discourse analysis we reveal the sociocultural diversity of the scientists. If you want to attract audience’s attention to your scientific research, narratives should be integrated into your scientific discourse. Those who understand this consistent pattern are considered the leading scientists. Taking into account that it is prestigious to be renowned, celebrated in science, it is a covert prestige to write narratives in science. We define a science narrative as the intentional, consequent, coherent, event discourse or a discourse fragment, which contains the author creativity, in some cases intrigue, and gives mostly qualitative information (compared with quantitative data) in order to provide maximum understanding of the research. Science narratives also allow the effective argumentation and consequently construct the identity of the persuasive narrator. However, skills of creating appropriate scientific discourse reflect the level of prestige. In order to teach postgraduate students to be successful in English scientific writing and to be prestigious in the scientific society, we have defined the science narrative and outlined its main features and characteristics. Narratives contribute to audience’s involvement with the narrator and his/her narration. In general, the way in which a narrative is performed may result in (limited or greater) contact with the audience. To gain these aim authors use emotional fictional elements; descriptive elements: adjectives; adverbs; comparisons and so on; author’s evaluative elements. Thus, the features of science narrativity are the following: descriptive tools; authors evaluation; qualitative information exceeds the quantitative data; facts take the event status; understandability; accessibility; creativity; logics; intrigue; esthetic nature; fiction. To conclude, narratives function covert prestige of the scientific discourse and shape the identity of the persuasive scientist.

Keywords: covert prestige, narrativity, scientific discourse, scientific narrative

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: M. Samadzadeh Mahabadi, J. Shanbehzadeh

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This paper presents a hybrid digital image-watermarking scheme, which is robust against varieties of attacks and geometric distortions. The image content is represented by important feature points obtained by an image-texture-based adaptive Harris corner detector. These feature points are extracted from LL2 of 2-D discrete wavelet transform which are obtained by using the Harris-Laplacian detector. We calculate the Fourier transform of circular regions around these points. The amplitude of this transform is rotation invariant. The experimental results demonstrate the robustness of the proposed method against the geometric distortions and various common image processing operations such as JPEG compression, colour reduction, Gaussian filtering, median filtering, and rotation.

Keywords: digital watermarking, geometric distortions, geometrical attack, Harris Laplace, important feature points, rotation, scale invariant feature

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Authors: Zikiou Nadia, Lahdir Mourad, Ameur Soltane

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In this paper, we propose an effective method for image compression based on SVM Regression (SVR), with three different kernels, and biorthogonal 2D Discrete Wavelet Transform. SVM regression could learn dependency from training data and compressed using fewer training points (support vectors) to represent the original data and eliminate the redundancy. Biorthogonal wavelet has been used to transform the image and the coefficients acquired are then trained with different kernels SVM (Gaussian, Polynomial, and Linear). Run-length and Arithmetic coders are used to encode the support vectors and its corresponding weights, obtained from the SVM regression. The peak signal noise ratio (PSNR) and their compression ratios of several test images, compressed with our algorithm, with different kernels are presented. Compared with other kernels, Gaussian kernel achieves better image quality. Experimental results show that the compression performance of our method gains much improvement.

Keywords: image compression, 2D discrete wavelet transform (DWT-2D), support vector regression (SVR), SVM Kernels, run-length, arithmetic coding

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Authors: M. M. Ali, Ahmed Al- Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed the new image-based non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. Plants were allowed to grow on nutrient media containing different P concentrations, i.e. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P as NaH2PO4). After 10 weeks of growth, plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. This data was further used in the linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using the image and morphological data. Our proposed non-destructive imaging method is precise in estimating P requirements of different crop species.

Keywords: image-based techniques, leaf area, leaf P contents, linear discriminant analysis

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Authors: Siti Salbiah Samsudin, Hamzah Arof, Ainuddin Wahid Abdul Wahab, Mohd Yamani Idna Idris

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Standard X-ray spine images produced by conventional screen-film technique have a limited field of view. This limitation may obstruct a complete inspection of the spine unless images of different parts of the spine are placed next to each other contiguously to form a complete structure. Another solution to producing a whole spine image is by assembling the digitized x-ray images of its parts automatically using image stitching. This paper presents a new Medical Image Stitching (MIS) method that utilizes Minimum Average Correlation Energy (MACE) filters to identify and merge pairs of x-ray medical images. The effectiveness of the proposed method is demonstrated in two sets of experiments involving two databases which contain a total of 40 pairs of overlapping and non-overlapping spine images. The experimental results are compared to those produced by the Normalized Cross Correlation (NCC) and Phase Only Correlation (POC) methods for comparison. It is found that the proposed method outperforms those of the NCC and POC methods in identifying both the overlapping and non-overlapping medical images. The efficacy of the proposed method is further vindicated by its average execution time which is about two to five times shorter than those of the POC and NCC methods.

Keywords: image stitching, MACE filter, panorama image, scoliosis

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Authors: Razan Farah, Siham Ballah

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Facebook, Instagram, TikTok and other social media applications have become an integral component of everyone’s social life, particularly among younger generations and adolescences. These social apps have been changing a lot of conceptions and believes in the population by representing public figures and celebrities as role models. The social comparison theory, which says that people self-evaluate based on comparisons with similar others, is commonly used to explore the impact of social media on body image. There is a need to study the influence of those social platforms on the body image as there have been an increase in body dissatisfaction in the recent years. This cross sectional study used a self administered questionnaire on a simple random sample of 133 female medical students of the first year. Finding shows that the response rate was 75%. There was an association between social media usage and noticing how the person look(p value = .022), but no significant association between social media use and body image influence or dissatisfaction was found. This study implies more research under this topic in Sudan as the literature are scarce.

Keywords: body image, body dissatisfaction, social media, adolescences

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Authors: Yeimy L. Quintana, Juan G. Zuluaga, Sandra S. Arango

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The comet assay is a method based on electrophoresis that is used to measure DNA damage in cells and has shown important results in the identification of substances with a potential risk to the human population as innumerable physical, chemical and biological agents. With this technique is possible to obtain images like a comet, in which the tail of these refers to damaged fragments of the DNA. One of the main problems is that the image has unequal luminosity caused by the fluorescence microscope and requires different processing to condition it as well as to know how many optimal comets there are per sample and finally to perform the measurements and determine the percentage of DNA damage. In this paper, we propose the design and implementation of software using Image Processing Toolbox-MATLAB that allows the automation of image processing. The software chooses the optimum comets and measuring the necessary parameters to detect the damage.

Keywords: artificial vision, comet assay, DNA damage, image processing

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Authors: Aditya Soni, Nimesh Parikh, R. A. Thakrar

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Background: A cross-sectional study looked to focus body image satisfaction, heretofore under investigated arena in our setting. This study additionally examined the relationship of body mass index, influence of media and self-esteem. Our second objective was to assess whether there was any relationship between body image dissatisfaction and gender. Methods: A cross-sectional study using body image satisfaction described in words was undertaken, which also explored relationship with body mass index (BMI), influence of media, self-esteem and other selected co-variables such as socio-demographic details, overall satisfaction in life, and particularly in academic/professional life, current health status using 5-item based Likert scale. Convenience sampling was used to select participants of both genders aged from 17 to 32 on a sample size of 303 participants. Results : The body image satisfaction had significant relationship with Body mass index (P<0.001), eating attitude (P<0.001), influence of media (P<0.001) and self-esteem (P<0.001). Students with low weight had a significantly higher prevalence of body image satisfaction while overweight students had a significantly higher prevalence of dissatisfaction (P<0.001). Females showed more concern about body image as compared to males. Conclusions: Generally, this study reveals that the eating attitude, influence of the media and self-esteem is significantly related to the body image. On an empowering note, this level needs to be saved for overall mental and sound advancement of people. Proactive preventive measures could be started in foundations on identity improvement, acknowledgement of self and individual contrasts while keeping up ideal weight and dynamic life style.

Keywords: body image, body mass index, media, self-esteem

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Authors: S. Vignesh, K. S. Rangasamy

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The paper deals with the device capable of detecting and disabling digital cameras. The system locates the camera and then neutralizes it. Every digital camera has an image sensor known as a CCD, which is retro-reflective and sends light back directly to its original source at the same angle. The device shines infrared LED light, which is invisible to the human eye, at a distance of about 20 feet. It then collects video of these reflections with a camcorder. Then the video of the reflections is transferred to a computer connected to the device, where it is sent through image processing algorithms that pick out infrared light bouncing back. Once the camera is detected, the device would project an invisible infrared laser into the camera's lens, thereby overexposing the photo and rendering it useless. Low levels of infrared laser neutralize digital cameras but are neither a health danger to humans nor a physical damage to cameras. We also discuss the simplified design of the above device that can used in theatres to prevent piracy. The domains being covered here are optics and image processing.

Keywords: CCD, optics, image processing, D3CIP

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Authors: Ersin Bozkurt

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The aim of the study is to develop materials for understanding image formations through virtual objects in geometric optics. The images in physics course books are formed by using real objects. This results in mistakes in the features of images because of generalizations which leads to conceptual misunderstandings in learning. In this study it was intended to identify pre-service physics teachers misunderstandings arising from false generalizations. Focused group interview was used as a qualitative method. The findings of the study show that students have several misconceptions such as "the image in a plain mirror is always virtual". However a real image can be formed in a plain mirror. To explain a virtual object's image formation in a more understandable way an overhead projector and episcope and their design was illustrated. The illustrations are original and several computer simulations will be suggested.

Keywords: computer simulations, geometric optics, physics education, students' misconceptions in physics

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Authors: Latha Subbiah, Dhanalakshmi Samiappan

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In this paper, we propose denoising Common Carotid Artery (CCA) B mode ultrasound images by a decomposition approach to curvelet thresholding and automatic segmentation of the intima media thickness and adventitia boundary. By decomposition, the local geometry of the image, its direction of gradients are well preserved. The components are combined into a single vector valued function, thus removes noise patches. Double threshold is applied to inherently remove speckle noise in the image. The denoised image is segmented by active contour without specifying seed points. Combined with level set theory, they provide sub regions with continuous boundaries. The deformable contours match to the shapes and motion of objects in the images. A curve or a surface under constraints is developed from the image with the goal that it is pulled into the necessary features of the image. Region based and boundary based information are integrated to achieve the contour. The method treats the multiplicative speckle noise in objective and subjective quality measurements and thus leads to better-segmented results. The proposed denoising method gives better performance metrics compared with other state of art denoising algorithms.

Keywords: curvelet, decomposition, levelset, ultrasound

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Authors: Biji Jacob

Abstract:

Vector quantization algorithm which uses minimum distance calculation for codebook generation, a time consuming calculation performed on each pixel values leads to computation complexity. The codebook is updated by comparing the distance of each vector to their centroid vector and measure for their closeness. In this paper vector quantization is modified based on vector difference algorithm for image enhancement purpose. In the proposed scheme, vector differences between the vectors are considered as the new generation vectors or new codebook vectors. The codebook is updated by comparing the new generation vector with a threshold value having minimum error with the parent vector. The minimum error decides the fitness of each newly generated vector. Thus the codebook is generated in an adaptive manner and the fitness value is determined for the suppression of the degraded portion of the image and thereby leads to the enhancement of the image through the adaptive searching capability of the vector quantization through vector difference algorithm. Experimental results shows that the vector difference scheme efficiently modifies the vector quantization algorithm for enhancing the image with peak signal to noise ratio (PSNR), mean square error (MSE), Euclidean distance (E_dist) as the performance parameters.

Keywords: codebook, image enhancement, vector difference, vector quantization

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Authors: Yasuyuki Takahashi, Hayato Ishimura, Masao Miyagawa, Teruhito Mochizuki

Abstract:

Quantitative measurement of myocardium perfusion is possible with single photon emission computed tomography (SPECT) using a semiconductor detector. However, accumulation of ^99mTc-tetrofosmin in the liver may make it difficult to assess that accurately in the inferior myocardium. Our idea is to reduce the high accumulation in the liver by using dynamic SPECT imaging and a technique called time subtraction. We evaluated the performance of a new SPECT system with a cadmium-zinc-telluride solid-state semi- conductor detector (Discovery NM 530c; GE Healthcare). Our system acquired list-mode raw data over 10 minutes for a typical patient. From the data, ten SPECT images were reconstructed, one for every minute of acquired data. Reconstruction with the semiconductor detector was based on an implementation of a 3-D iterative Bayesian reconstruction algorithm. We studied 20 patients with coronary artery disease (mean age 75.4 ± 12.1 years; range 42-86; 16 males and 4 females). In each subject, 259 MBq of ^99mTc-tetrofosmin was injected intravenously. We performed both a phantom and a clinical study using dynamic SPECT. An approximation to a liver-only image is obtained by reconstructing an image from the early projections during which time the liver accumulation dominates (0.5~2.5 minutes SPECT image-5~10 minutes SPECT image). The extracted liver-only image is then subtracted from a later SPECT image that shows both the liver and the myocardial uptake (5~10 minutes SPECT image-liver-only image). The time subtraction of liver was possible in both a phantom and the clinical study. The visualization of the inferior myocardium was improved. In past reports, higher accumulation in the myocardium due to the overlap of the liver is un-diagnosable. Using our time subtraction method, the image quality of the ^99mTc-tetorofosmin myocardial SPECT image is considerably improved.

Keywords: 99mTc-tetrofosmin, dynamic SPECT, time subtraction, semiconductor detector

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Authors: Yu Zhang, Kohei Inoue, Kiichi Urahama

Abstract:

We propose a simplified bilateral filter with binarized coefficients for accelerating it. Its computational cost is further decreased by sampling pixels. This computationally low cost filter is useful for smoothing or denoising images by using mobile devices with limited computational power.

Keywords: bilateral filter, binarized-weight bilateral filter, image smoothing, image denoising, pixel sampling

Procedia PDF Downloads 469