Machine Vision for Inspection and Measurement contains the proceedings of the Second Annual Workshop on Machine Vision sponsored by the Center for Computer Aids for Industrial Productivity (CAIP) at Rutgers University and held on April 25-26, 1988 in New Brunswick, New Jersey. The papers explore the application of machine vision to inspection and measurement and cover topics such as the problem of object-pose estimation and depth recovery through inverse optics. The use of machine vision techniques in inspection of integrated circuits and semiconductor wafers is also discussed. Comprised of 11 chapters, this book opens with the problem of using fine-grained parallel machines for VLSI inspection. The discussion then turns to a variety of real-life applications of machine vision, including inspection of integrated circuits, semiconductor wafers, TV-tube glass, and mechanical parts. The use of machine vision to measure the curvature of the human cornea for vision correction and contact lens fitting purposes is also considered. The remaining chapters focus on motion estimation from stereo sequences using orthographic-view algorithms; photometric sampling for determining surface shape and reflectance; and efficient depth recovery by means of inverse optics. A chapter addresses the question of whether the industry is ready for machine vision and comes up with some optimistic predictions. This monograph will be of interest to practitioners in the fields of computer science and applied mathematics.

Machine Vision for Inspection and Measurement contains the proceedings of the Second Annual Workshop on Machine Vision sponsored by the Center for Computer Aids for Industrial Productivity (CAIP) at Rutgers University and held on April 25-26, 1988 in New Brunswick, New Jersey. The papers explore the application of machine vision to inspection and measurement and cover topics such as the problem of object-pose estimation and depth recovery through inverse optics. The use of machine vision techniques in inspection of integrated circuits and semiconductor wafers is also discussed. Comprised of 11 chapters, this book opens with the problem of using fine-grained parallel machines for VLSI inspection. The discussion then turns to a variety of real-life applications of machine vision, including inspection of integrated circuits, semiconductor wafers, TV-tube glass, and mechanical parts. The use of machine vision to measure the curvature of the human cornea for vision correction and contact lens fitting purposes is also considered. The remaining chapters focus on motion estimation from stereo sequences using orthographic-view algorithms; photometric sampling for determining surface shape and reflectance; and efficient depth recovery by means of inverse optics. A chapter addresses the question of whether the industry is ready for machine vision and comes up with some optimistic predictions. This monograph will be of interest to practitioners in the fields of computer science and applied mathematics.

Machine Vision for Inspection and Measurement contains the proceedings of the Second Annual Workshop on Machine Vision sponsored by the Center for Computer Aids for Industrial Productivity (CAIP) at Rutgers University and held on April 25-26, 1988 in New Brunswick, New Jersey. The papers explore the application of machine vision to inspection and measurement and cover topics such as the problem of object-pose estimation and depth recovery through inverse optics. The use of machine vision techniques in inspection of integrated circuits and semiconductor wafers is also discussed. Comprised of 11 chapters, this book opens with the problem of using fine-grained parallel machines for VLSI inspection. The discussion then turns to a variety of real-life applications of machine vision, including inspection of integrated circuits, semiconductor wafers, TV-tube glass, and mechanical parts. The use of machine vision to measure the curvature of the human cornea for vision correction and contact lens fitting purposes is also considered. The remaining chapters focus on motion estimation from stereo sequences using orthographic-view algorithms; photometric sampling for determining surface shape and reflectance; and efficient depth recovery by means of inverse optics. A chapter addresses the question of whether the industry is ready for machine vision and comes up with some optimistic predictions. This monograph will be of interest to practitioners in the fields of computer science and applied mathematics.