Analysis of methods for image rearrangement

Kevin G. Harding

doi:10.1117/12.169364

15 March 1994 Analysis of methods for image rearrangement

Kevin G. Harding

Proceedings Volume 2065, Optics, Illumination, and Image Sensing for Machine Vision VIII; (1994) https://doi.org/10.1117/12.169364
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States

Abstract

A problem which is often encountered in machine vision applications is trying to view a long narrow or other odd shaped field with a rectangular video sensor. A variety of approaches have been demonstrated in the past to reconfigure a long image to better match the sensor format. The use of mirrors and beamsplitters is perhaps the most obvious of these approaches. However, the use of special prisms, such as rhombs and tyneoscopes offer some interesting solutions. A very versatile method we investigated is to use multiple lenses along the length of the part, which then feed one larger collection lens. The result of this lens system is to break a single long line into 4 or more segments which are presented as parallel lines on the video sensor. The merits, limitations, and potential applications of this lens based technique in comparison to the prism based methods described are discussed in this paper.

Citation Download Citation

Kevin G. Harding "Analysis of methods for image rearrangement", Proc. SPIE 2065, Optics, Illumination, and Image Sensing for Machine Vision VIII, (15 March 1994); https://doi.org/10.1117/12.169364

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available