A Beginner’s Guide to Image Multi-Level Thresholding emphasizes various image thresholding methods that are necessary for image pre-processing and initial level enhancement.
- Explains basic concepts and the implementation of Image Multi-Level Thresholding (grayscale and RGB images)
- Presents a detailed evaluation in real-time application, including the need for heuristic algorithm, the choice of objective and threshold function, and the evaluation of the outcome
- Describes how the image thresholding acts as a pre-processing technique and how the region of interest in a medical image is enhanced with thresholding
- Illustrates integration of the thresholding technique with bio-inspired algorithms
- Includes current findings and future directions of image multi-level thresholding and its practical implementation
- Emphasizes the need for multi-level thresholding with suitable examples
The book is aimed at graduate students and researchers in image processing, electronics engineering, computer sciences and engineering.
Table of Contents
1. Introduction 2. Thresholding Approaches 3. Grayscale and RGB-scale Image Examination 4. Heuristic Algorithm Assisted Thresholding 5. Objective Function and Image Quality Measures 6. Assessment of Images with Constraints 7. Thresholding of Benchmark Images 8. Thresholding of Biomedical Images 9. Thresholding of Plant-Weed images 10. Conclusion
Dr. Venkatesan Rajinikanth is a Professor in the Department of Electronics and Instrumentation Engineering at St. Joseph's College of Engineering, Chennai, India. Recently he edited a book titled Advances in Artificial Intelligence Systems, published by Nova Science Publishers, USA. He is the Associate Editor of Int. J. of Rough Sets and Data Analysis (IGI Global, US, DBLP, ACM dl) and edits special issues in the following journals: Current Signal Transduction Therapy, Current Medical Imaging Reviews, and International Journal of Swarm Intelligence Research. His main research interests include medical imaging, machine learning, and computer aided diagnosis as well as data mining.
Dr. Nadaradjane Sri Madhava Raja is passionate about teaching. He has 17 years of teaching experience at various engineering colleges. Currently, he is an Associate Professor at St. Joseph's College of Engineering, Chennai, India. He earned his doctorate in 2014, in the area of biomedical engineering. He completed his post-graduation in process control and instrumentation in 2002. His under graduate degree is in electrical and electronics engineering in 2001. Dr. Raja is also an ardent researcher and his major areas of research are medical image processing, optimization algorithms, heuristic algorithms, and biomechanics. He has published over 50 research papers in renowned journals and conference proceedings. He has also contributed chapters on optimization techniques to books published Nova Science Publishers, USA.
Nilanjan Dey is an Asso. Professor, Department of Computer Science and Engineering, JIS University, Kolkata, India. He is a visiting fellow of the University of Reading, UK. He was an honorary Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012-2015). He was awarded his PhD. from Jadavpur Univeristy in 2015. He has authored/edited more than 70 books with Elsevier, Wiley, CRC Press and Springer, and published more than 300 papers. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, IGI Global, Associated Editor of IEEE Access and International Journal of Information Technology, Springer. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing, Springer, Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare, Elsevier, Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal processing and data analysis, CRC. His main research interests include Medical Imaging, Machine learning, Computer Aided Diagnosis, Data Mining etc. He is the Indian Ambassador of International Federation for Information Processing – Young ICT Group and Senior member of IEEE.