Object-Based Segmentation And Color Recognition In Multispectral Images

Michael H. Brill

doi:10.1117/12.952684

29 March 1989 Object-Based Segmentation And Color Recognition In Multispectral Images

Michael H. Brill

Proceedings Volume 1076, Image Understanding and the Man-Machine Interface II; (1989) https://doi.org/10.1117/12.952684
Event: OE/LASE '89, 1989, Los Angeles, CA, United States

Abstract

It is difficult to segment an image according to object, for the geometry of lighting and viewing of three-dimensional objects incurs spatial inhomogeneities (highlights, shading, and cast shadows) in the image. However, the bands of a multispectral image can be used to do the segmentation. We start by assuming that the image field for a uniformly colored object is the sum of a small number of terms, each term being the product of a spatial and a spectral part. The physics of the spatial part is intricate, but the spatial part can be factored out to produce several space-invariant fields of numbers within reflectance boundaries. For an image field either from two light sources on a matte surface or from a single light source on a dielectric surface with highlights, the space-invariant quantities characterizing the object are the components of a particular unit vector in color space. The possibility is discussed of an algorithm for estimating the relative spectral reflectance of an object based on its space-invariant image fields.

Citation Download Citation

Michael H. Brill "Object-Based Segmentation And Color Recognition In Multispectral Images", Proc. SPIE 1076, Image Understanding and the Man-Machine Interface II, (29 March 1989); https://doi.org/10.1117/12.952684

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