Introduction to the world of computer vision
- 1. SHREE HANUMAN VYAYAM PRASARAK MANDAL’S DEGREE COLLEGE OF PHYSICAL EDUCATION, AMRAVATI (Multi-Faculty Autonomous College) Academic session 2023-2024 SEMINAR ON “COMPUTER VISION” SUBMITTED BY Mr. Dhiraj S. Parale BCA III (Sem-I) GUIDED BY Prof. J. M. Kale Dept. of Computer Science
- 2. CONTENTS 1) INTRODUCTIONS 2) HISTORY 3) HOW COMPUTER VISION IT WORKS ? 4) APPLICATIONS 5) FEATURES 6) TYPICAL TASK 7) ADVANTAGES 8) DISADVANTAGES 9) FUTURE SCOPE 10) CONCLUSION 11) REFERENCES
- 3. INTRODUCTION Computer Vision is field of AI. The goal of computer vision is to understand the content of digital images. Typically, this involves developing methods that attempt to reproduce the capability of human vision.
- 4. HISTORY Computer vision began in earnest during the 1960s at universities that viewed the project as a stepping stone to Artificial Intelligence. Early researchers were extremely optimistic about the future of these related fields and promoted Artificial Intelligence as a technology that could transform the world. 1959 :- Neurophysiologists discover the human vision hierarchical. 1963 :- AI was in academic field 1974 :- Optical Character Recognition (OCR) was introduced.
- 5. Image :- The History of Computer Vision 2000-2001 :- Studies on Object Recognition 2010 :- CNN and other deep learning models are used
- 6. HOW COMPUTER VISION IT WORKS It has several stages they are Image Acquisition :- Image acquisition refers to the process of capturing visual data through cameras or other sensors. Image Processing :- The goal of image processing is to prepare the visual data for further analysis.
- 7. Feature Extraction :- Feature extraction involves identifying key elements in an image, such as lines, shapes, and textures. Pattern recognition :- A data analysis method that uses machine learning algorithms to automatically recognize patterns. Fig :- Pattern recognition
- 8. APPLICATION DEFENSE AND SECURITY HEALTHCARE ROBOTICS MEDIA
- 9. FEATURES Text Extraction Image Understanding Digital Image Processing Object Detection
- 10. TYPICAL TASK All of these are Computer Vision tasks. Visual Relationship Detection Image Captioning Image Reconstruction or Image Inpainting Face Recognition
- 11. ADVANTAGES There are four main advantages of computer vision: Process in a simpler and faster way Accuracy A wide range of use The reduction of costs
- 12. DISADVANTAGES We have to consider some disadvantages: Necessity of specialists Spoiling Failing in image processing
- 13. FUTURE SCOPE COMPUTER VISION carrying out a greater number of tasks in the future. Skills Required Exceptional device computing abilities Solid understanding of database systems Knowledge of programming languages and libraries such as C++, Matlab, Python, SQL Server, OpenCV, R, and others. Troubleshooting abilities
- 14. CONCLUSION Computer Vision is a powerful and fast-growing technology i.e already used in many areas of our lives, from autonomous vehicles to facial recognition. It has the potential to benefit humanity in variety of ways.
- 15. REFERENCES Websites : 1. https://www.slideshare.net/shivakrishnashekar/computer-vision-25544251 2. https://www.sciencedirect.com/topics/food-science/computer-vision-technolog y 3. https://www.simplilearn.com/computer-vision-article 4. https://en.wikipedia.org/wiki/Computer_vision 5. https://machinelearningmastery.com/what-is-computer-vision Books : 1. Stuart Russell, “A modern Approach”, Published in 1995 2. Richard Szeliski , “Algorithms and Application”, Published in 19 October 2010 3. Simon J. D. Prince , “Models Learning and Inference”, Published in 18 June 2012