Surface Characteristics Measurement Using Computer Vision: A Review

Computer vision provides image-based solutions to inspect and investigate the quality of the surface to be measured. For any components to execute their intended functions and operations, surface quality is considered equally significant to dimensional quality. Surface Roughness (Ra) is a widely recognized measure to evaluate and investigate the surface quality of machined parts. Various conventional methods and approaches to measure the surface roughness are not feasible and appropriate in industries claiming 100% inspection and examination because of the time and efforts involved in performing the measurement. However, Machine vision has emerged as the innovative approach to executing the surface roughness measurement. It can provide economic, automated, quick, and reliable solutions. This paper discusses the characterization of the surface texture of surfaces of traditional or non-traditional manufactured parts through a computer/machine vision approach and assessment of the surface characteristics, i.e., surface roughness, waviness, flatness, surface texture, etc., machine vision parameters. This paper will also discuss multiple machine vision techniques for different manufacturing processes to perform the surface characterization measurement.

Automated summary

Computer vision offers economic, automated, quick, and reliable solutions for inspecting and evaluating surface quality, especially in industries requiring 100% inspection. This paper discusses the characterization of surface texture of traditional or non-traditional manufactured parts using computer/machine vision methods and the assessment of machine vision parameters such as surface roughness, waviness, flatness, and surface texture.