Machine Vision Inspection Systems, Machine Learning-Based Approaches

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Machine Vision Inspection Systems (MVIS) is a multidisciplinary research field that emphasizes image processing, machine vision and, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry. Now a day's the current research on machine inspection gained more popularity among various researchers, because the manual assessment of the inspection may fail and turn into false assessment due to a large number of examining while inspection process.
This volume 2 covers machine learning-based approaches in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT), presence/absence detection, defect/fault detection (weld, textile, tiles, wood, etc.,), automated vision test & measurement, pattern matching, optical character recognition & verification (OCR/OCV), natural language processing, medical diagnosis, etc. This edited book is designed to address various aspects of recent methodologies, concepts, and research plan out to the readers for giving more depth insights for perusing research on machine vision using machine learning-based approaches.

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52. Nayak, S.R., Mishra, J., Palai, G., A modified approach to estimate fractal dimension of gray scale images. Optik, 161, 136–145, 2018.

53. Jena, K.K., Nayak, S.R., Mishra, S., Mishra, S.N., Vehicle Number Plate Detection: An Edge Image Based Approach, in: 4th Springer International Conference on Advanced Computing and Intelligent Engineering, Advances in Intelligent Systems and Computing , 2019.

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