COMPUTER VISION: IMAGE RECOGNITION AND ANALYSIS TECHNIQUES

Prof. Munindra Lunagaria · Mr. Yogesh Kumar Podapati · Dr. Sheshang D. Degadwala · Saikumar Tara

Jul 2023 · Xoffencerpublication

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220

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Computer vision is what we call the practice of using computer-based imaging where there is no human interaction in the visual loop at any point in the process. The photos are analyzed by a computer, which then takes appropriate action depending on their results. Computer vision systems are used in a variety of medical disciplines, and the only thing that can be said with absolute confidence is that the scope of these systems' applications will continue to expand in the future is the only thing that can be declared with absolute certainty. processing one or more digital photographs in order to generate valuable inferences about real-world physical objects and situations by computing the features of the 3D environment. This processing may be done with either one picture or all of them together. generating an accurate and comprehensive description of a real world object based on a photograph of that thing. The discipline of computer vision came into being as a consequence of efforts to model image processing utilizing the several approaches that are accessible within the discipline of machine learning. The field of computer vision makes use of machine learning to search for patterns in images with the end goal of deciphering such patterns. The field of computer vision entails the practice of teaching computers to recognize objects based on the digital still photos or moving movies that are sent into them. Finding methods through which jobs can be automated that now rely on the human visual system is the objective here. Image processing is one of the various methods that are utilized in the execution of this approach. The subfield of artificial intelligence (AI) known as computer vision is an absolutely necessary component in order for computers and other types of systems to be able to respond or provide suggestions based on visual data such as digital photos, movies, and other types of inputs. The same way that artificial intelligence makes it possible for computers to think, computer vision makes it possible for computers to see, comprehend, and observe. Computer vision and human vision are functionally comparable; the primary difference is that human eyesight developed far earlier than computer vision. The capacity of human beings to learn to differentiate between different things, their distances from one another, whether or not the items are moving

About the author

Prof. Munindra Lunagaria is Working as an Assistant Professor in Department of Computer Engineering at Marwadi University Rajkot. Also, a Ph.D. Research Scholar at Marwadi university Rajkot. Also having 14 years of Academic experience. Area of Expertise are, Database, Web Programming, Information Security, and Current research interest in AI, ML, DL.

Mr. Yogesh Kumar Podapati is a seasoned Data Scientist with a wealth of experience in all phases of the software technology development life cycle. As an expert in the field of AI and Machine Learning, he specializes in facilitating collaboration and optimization across technical and business domains to develop robust solutions. Yogesh has a strong background in automating sensitive data and services, both on premise and on the cloud, using software engineering and AI mechanisms. His contributions to the field of automation have helped drive efficiency in the IT sector across the board. With his exceptional skills and in-depth knowledge of the field, Yogesh is a highly sought-after professional in the data science community.

Dr. Sheshang D. Degadwala is presently working as Associate Professor and Head of Computer Engineering Department, Sigma University , Vadodara. He has published 235 research papers in reputed international journals and conferences including IEEE, Elsevier and Springer. His main research work focuses on Image Processing, Computer Vision, Information Security, Theory of Computation and Data Mining. He is also Microsoft Certified in Python Programming and Excel. He has published 18 books and he got grant for 3 patent. He has published 125 Indian Patent. He has received 50 awards for academic and research achievement.

Saikumar Tara, working in the Dept of ECE, BVRIT HYDERABAD College of Engineering for Women (Autonomous), Hyderabad. Saikumar Tara, Senior IEEE member, Gold Medal recipient from JNTUH's Ex VC, Dr. D N Reddy, for his B.Tech degree in Academics on Feb 28, 2008, and University Topper for M.Tech degree from Kakatiya Institute of Technology and Science (KITS Warangal), Kakatiya University Warangal in 2010. He is an experienced IEEE Transaction Reviewer on Fuzzy Systems (TFS) and IEEE Transactions on Emerging Topics in Computational Intelligence, USA. He is an active volunteer in IEEE Hyderabad Section and served as SAC Chairman, IEEE Hyderabad Section, He delivered around 25 -30 plus talks at various places. He is an International Workshop Advisory Group, IEEE Conference, and Publisher for several indexed Scopus journals. He has 50-plus articles in International Journals, Book Chapters, and Conferences, as well as 20 plus regional conference articles. To his name, he holds nine patents.

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