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Model for image sensing and digitization in machine vision

  • Stony Brook University

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations

Abstract

A mathematical model for a typical CCD camera system used in machine vision applications is presented. This model is useful in research and development of machine vision systems, and in the computer simulation of camera systems. The model has been developed with the intention of using it to investigate algorithms for recovering depth from image blur. However, the model is general and can be used to address other problems in machine vision. The model is based on a precise definition of input to the camera system. This definition decouples the photometric properties of a scene from the geometric properties of the scene in the input to the camera system. An ordered sequence of about 20 operations are defined which transform the camera system's input to its output, i.e. digital image data. Each operation in the sequence usually defines the effect of one component of the camera system on the input. This model underscores the complexity of the actual imaging process which is routinely underestimated and oversimplified in machine vision research.

Original languageEnglish
Pages (from-to)70-84
Number of pages15
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume1385
StatePublished - 1991
EventOptics, Illumination, and Image Sensing for Machine Vision V - Boston, MA, USA
Duration: Nov 8 1990Nov 9 1990

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