Surface Characteristics Measurement Using Computer Vision:A Review

作     者：AbdulWahab Hashmi Harlal Singh Mali Anoj Meena Mohammad Farukh Hashmi Neeraj Dhanraj Bokde 

作者机构：Department of Mechanical EngineeringAdvanced Manufacturing and Mechatronics LabMalaviya National Institute of TechnologyJaipur302017India Department of Electronics and Communication EngineeringNational Institute of TechnologyWarangal506004India Department of Civil and Architectural EngineeringAarhus UniversityAarhus8000Denmark Center for Quantitative Genetics and GenomicsAarhus UniversityAarhus8000Denmark 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2023年第135卷第5期

页      面：917-1005页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：the Science and Engineering Research Board Department of Science and Technology Government of India for supporting this work through the Grant DST-SERB EMR/2016/003372 

主　　题：Machine vision surface roughness computer vision machining parameters surface characterization 

摘      要：Computer vision provides image-based solutions to inspect and investigate the quality of the surface to be *** any components to execute their intended functions and operations,surface quality is considered equally significant to dimensional *** Roughness(Ra)is a widely recognized measure to evaluate and investigate the surface quality of machined *** 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 ***,Machine vision has emerged as the innovative approach to executing the surface roughness *** can provide economic,automated,quick,and reliable *** 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 *** paper will also discuss multiple machine vision techniques for different manufacturing processes to perform the surface characterization measurement.