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Methods And Systems For Performing Segmentation And Registration Of Images Using Neutrosophic Similarity Scores
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Book Synopsis METHODS AND SYSTEMS FOR PERFORMING SEGMENTATION AND REGISTRATION OF IMAGES USING NEUTROSOPHIC SIMILARITY SCORES by : Yanhui Guo
Download or read book METHODS AND SYSTEMS FOR PERFORMING SEGMENTATION AND REGISTRATION OF IMAGES USING NEUTROSOPHIC SIMILARITY SCORES written by Yanhui Guo and published by Infinite Study. This book was released on with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: An example method for segmenting an object contained in an image includes receiving an image including a plurality of pixels , transforming a plurality of characteristics of a pixel into respective neutrosophic set domains , calculating a neutrosophic similarity score for the pixel based on the respective neutrosophic set domains for the characteristics of the pixel , segmenting an object from background of the image using a region growing algorithm based on the neutrosophic similarity score for the pixel , and receiving a margin adjustment related to the object segmented from the background of the image .
Book Synopsis An Efficient Image Segmentation Algorithm Using Neutrosophic Graph Cut by : Yanhui Guo
Download or read book An Efficient Image Segmentation Algorithm Using Neutrosophic Graph Cut written by Yanhui Guo and published by Infinite Study. This book was released on with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Segmentation is considered as an important step in image processing and computer vision applications, which divides an input image into various non-overlapping homogenous regions and helps to interpret the image more conveniently. This paper presents an efficient image segmentation algorithm using neutrosophic graph cut (NGC).
Book Synopsis Neutrosophic Set in Medical Image Analysis by : Yanhui Guo
Download or read book Neutrosophic Set in Medical Image Analysis written by Yanhui Guo and published by Academic Press. This book was released on 2019-08-08 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set’s novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis. Introduces the mathematical model and concepts of neutrosophic theory and methods Highlights the different techniques of neutrosophic theory, focusing on applying the neutrosophic set in image analysis to support computer- aided diagnosis (CAD) systems, including approaches from soft computing and machine learning Shows how NS techniques can be applied to medical image denoising, segmentation and classification Provides challenges and future directions in neutrosophic set based medical image analysis
Book Synopsis Applications of Neutrosophic Sets in Medical Image Denoising and Segmentation by : DEEPIKA KOUNDAL
Download or read book Applications of Neutrosophic Sets in Medical Image Denoising and Segmentation written by DEEPIKA KOUNDAL and published by Infinite Study. This book was released on with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: In medical science, diagnosis and prognosis is one of the most difficult and challenging task because of restricted subjectivity of the experts and presence of fuzziness in medical images. In observing the severity of several diseases, different professional experts may result in wrong diagnosis. In order to perform diagnosis intuitively in the medical images, different image processing methods have been explored in terms of neutrosophic theory to interpret the inherent uncertainty, ambiguity and vagueness. This paper demonstrates the use of neutrosophic theory in medical image denoising and segmentation where the performance is observed to be much better.
Book Synopsis APPROACH TO IMAGE SEGMENTATION BASED ON INTERVAL NEUTROSOPHIC SET by : Ye Yuan
Download or read book APPROACH TO IMAGE SEGMENTATION BASED ON INTERVAL NEUTROSOPHIC SET written by Ye Yuan and published by Infinite Study. This book was released on with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: As a generalization of the fuzzy set and intuitionistic fuzzy set, the neutrosophic set (NS) have been developed to represent uncertain, imprecise, incomplete and inconsistent information existing in the real world. Now the interval neutrosophic set (INS) which is an expansion of the neutrosophic set have been proposed exactly to address issues with a set of numbers in the real unit interval, not just one speci c number.
Book Synopsis New neutrosophic approach to image segmentation by : Yanhui Guo
Download or read book New neutrosophic approach to image segmentation written by Yanhui Guo and published by Infinite Study. This book was released on with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neutrosophic set (NS), a part of neutrosophy theory, studies the origin, nature and scope of neutralities, as well as their interactions with different ideational spectra. NS is a formal framework that has been recently proposed.
Book Synopsis An Adaptive Region Growing based on Neutrosophic Set in Ultrasound Domain for Image Segmentation by : XUE JIANG
Download or read book An Adaptive Region Growing based on Neutrosophic Set in Ultrasound Domain for Image Segmentation written by XUE JIANG and published by Infinite Study. This book was released on with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breast tumor segmentation in ultrasound is important for breast ultrasound (BUS) quantitative analysis and clinical diagnosis. Even this topic has been studied for a long time, it is still a challenging task to segment tumor in BUS accurately arising from difficulties of speckle noise and tissue background inconsistence. To overcome these difficulties, we formulate breast tumor segmentation as a classification problem in the neutrosophic set (NS) domain which has been previously studied for removing speckle noise and enhancing contrast in BUS images. The similarity set score and homogeneity value for each pixel have been calculated in the NS domain to characterize each pixel of BUS image. Based on that, the seed regions are selected by an adaptive Otsu-based thresholding method and morphology operations, then an adaptive region growing approach is developed for obtaining candidate tumor regions in NS domain.
Book Synopsis A Fast Image Segmentation Algorithm Based on Saliency Map and Neutrosophic Set Theory by : Sensen Song
Download or read book A Fast Image Segmentation Algorithm Based on Saliency Map and Neutrosophic Set Theory written by Sensen Song and published by Infinite Study. This book was released on with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to more or less deviations in the imaging system, there will be noise in the image, which makes the image segmentation inaccurate. To divide a natural image into a more accurate binary image, the target and background of the image are effectively separated to achieve a more effective segmentation result. Therefore, this paper proposes an image segmentation algorithm combining a saliency map and neutrosophic set (NS) theory. First, to overcome the problem of weak edges in the image, we highlight the details and use the guided filter to filter the various channels of the natural image. Then, the initial saliency map is generated. After the weighted superposition of the initial saliency map, the local entropy map and the gray scale map, the final saliency map can be generated using the nonlinear function, and it can effectively highlight the foreground information of the image. Second, the saliency map is transformed to the NS domain and interpreted by three subsets: true (T), indeterminate (I), and false (F). According to NS theory, the indeterminacy is reduced, and the segmentation results are finally obtained by using the method of threshold. Various experiments were done and compared with other state-of-the-art approaches. These experiments demonstrate the effect of the proposed work, which is fast and effective for de-noising.
Book Synopsis Statistical Methods for Coupling Expert Knowledge and Automatic Image Segmentation and Registration by : Ivan A. Kolesov
Download or read book Statistical Methods for Coupling Expert Knowledge and Automatic Image Segmentation and Registration written by Ivan A. Kolesov and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of the proposed research is to develop methods that couple an expert user's guidance with automatic image segmentation and registration algorithms. Often, complex processes such as fire, anatomical changes/variations in human bodies, or unpredictable human behavior produce the target images; in these cases, creating a model that precisely describes the process is not feasible. A common solution is to make simplifying assumptions when performing detection, segmentation, or registration tasks automatically. However, when these assumptions are not satisfied, the results are unsatisfactory. Hence, removing these, often times stringent, assumptions at the cost of minimal user input is considered an acceptable trade-off. Three milestones towards reaching this goal have been achieved. First, an interactive image segmentation approach was created in which the user is coupled in a closed-loop control system with a level set segmentation algorithm. The user's expert knowledge is combined with the speed of automatic segmentation. Second, a stochastic point set registration algorithm is presented. The point sets can be derived from simple user input (e.g. a thresholding operation), and time consuming correspondence labeling is not required. Furthermore, common smoothness assumptions on the non-rigid deformation field are removed. Third, a stochastic image registration algorithm is designed to capture large misalignments. For future research, several improvements of the registration are proposed, and an iterative, landmark based segmentation approach, which couples the segmentation and registration, is envisioned.
Book Synopsis Comparison of neutrosophic approach to various deep learning models for sentiment analysis by : Mayukh Sharma
Download or read book Comparison of neutrosophic approach to various deep learning models for sentiment analysis written by Mayukh Sharma and published by Infinite Study. This book was released on with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning has been widely used in numerous real-world engineering applications and for classification problems. Real-world data is present with neutrality and indeterminacy, which neutrosophic theory captures clearly. Though both are currently developing research areas, there has been little study on their interlinking. We have proposed a novel framework to implement neutrosophy in deep learning models. Instead of just predicting a single class as output, we have quantified the sentiments using three membership functions to understand them better. Our proposed model consists of two blocks, feature extraction, and feature classification.
Book Synopsis Optimization Theory Based on Neutrosophic and Plithogenic Sets by : Florentin Smarandache
Download or read book Optimization Theory Based on Neutrosophic and Plithogenic Sets written by Florentin Smarandache and published by Academic Press. This book was released on 2020-01-14 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization Theory Based on Neutrosophic and Plithogenic Sets presents the state-of-the-art research on neutrosophic and plithogenic theories and their applications in various optimization fields. Its table of contents covers new concepts, methods, algorithms, modelling, and applications of green supply chain, inventory control problems, assignment problems, transportation problem, nonlinear problems and new information related to optimization for the topic from the theoretical and applied viewpoints in neutrosophic sets and logic. All essential topics about neutrosophic optimization and Plithogenic sets make this volume the only single source of comprehensive information New and innovative theories help researchers solve problems under diverse optimization environments Varied applications address practitioner fields such as computational intelligence, image processing, medical diagnosis, fault diagnosis, and optimization design
Book Synopsis Neutrosophic Set - A Generalization of The Intuitionistic Fuzzy Set by : Florentin Smarandache
Download or read book Neutrosophic Set - A Generalization of The Intuitionistic Fuzzy Set written by Florentin Smarandache and published by Infinite Study. This book was released on 2010-08-23 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper one generalizes the intuitionistic fuzzy set (IFS), paraconsistent set, and intuitionistic set to the neutrosophic set (NS). Many examples are presented. Distinctions between NS and IFS are underlined.
Book Synopsis Feature Extraction and Image Processing for Computer Vision by : Mark Nixon
Download or read book Feature Extraction and Image Processing for Computer Vision written by Mark Nixon and published by Academic Press. This book was released on 2012-12-18 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature Extraction and Image Processing for Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the exemplar code of the algorithms." Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Adaboost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. Named a 2012 Notable Computer Book for Computing Methodologies by Computing Reviews Essential reading for engineers and students working in this cutting-edge field Ideal module text and background reference for courses in image processing and computer vision The only currently available text to concentrate on feature extraction with working implementation and worked through derivation
Book Synopsis Markov Processes for Stochastic Modeling by : Oliver Ibe
Download or read book Markov Processes for Stochastic Modeling written by Oliver Ibe and published by Newnes. This book was released on 2013-05-22 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. Presents both the theory and applications of the different aspects of Markov processes Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.
Book Synopsis Individual Tree Crown Delineation Using Multispectral LiDAR Data by : Faizaan Naveed
Download or read book Individual Tree Crown Delineation Using Multispectral LiDAR Data written by Faizaan Naveed and published by Infinite Study. This book was released on with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this study, multispectral Light Detection and Ranging (LiDAR) data were utilized to improve delineation of individual tree crowns (ITC) as an important step in individual tree analysis. A framework to integrate spectral and height information for ITC delineation was proposed, and the multi-scale algorithm for treetop detection developed in one of our previous studies was improved. In addition, an advanced region-based segmentation method that used detected treetops as seeds was proposed for segmentation of individual crowns based on their spectral, contextual, and height information.
Book Synopsis Pythagorean Fuzzy Sets by : Harish Garg
Download or read book Pythagorean Fuzzy Sets written by Harish Garg and published by Springer Nature. This book was released on 2021-07-22 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of recent research on topics related to Pythagorean fuzzy set, dealing with dynamic and complex decision-making problems. It discusses a wide range of theoretical and practical information to the latest research on Pythagorean fuzzy sets, allowing readers to gain an extensive understanding of both fundamentals and applications. It aims at solving various decision-making problems such as medical diagnosis, pattern recognition, construction problems, technology selection, and more, under the Pythagorean fuzzy environment, making it of much value to students, researchers, and professionals associated with the field.
Book Synopsis Advances in Communication Systems and Networks by : J. Jayakumari
Download or read book Advances in Communication Systems and Networks written by J. Jayakumari and published by Springer Nature. This book was released on 2020-06-13 with total page 837 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the selected peer-reviewed papers from the International Conference on Communication Systems and Networks (ComNet) 2019. Highlighting the latest findings, ideas, developments and applications in all areas of advanced communication systems and networking, it covers a variety of topics, including next-generation wireless technologies such as 5G, new hardware platforms, antenna design, applications of artificial intelligence (AI), signal processing and optimization techniques. Given its scope, this book can be useful for beginners, researchers and professionals working in wireless communication and networks, and other allied fields.
