Segmentation (Image Processing)

In image analysis, segmentation is the partition of a digital image into multiple regions (sets of pixels), according to some criterion. The goal of segmentation is typically to locate certain objects of interest which may be depicted in the image. Segmentation could therefore be seen as a computer vision problem. Unfortunately, many important segmentation algorithms are too simple to solve this problem accurately: they compensate for this limitation with their predictability, generality, and efficiency. A simple example of segmentation is thresholding a grayscale image with a fixed threshold t: each pixel p is assigned to one of two classes, P0 or P1, depending on whether I(p) < t or I(p) ≥ t. Some other segmentation algorithms are based on segmenting images into regions of similar texture according to wavelet or Fourier transforms. Segmentation criteria can be arbitrarily complex, and take into account global as well as local criteria. A common requirement is that each region must be connected in some sense.

 

<< PreviousWord BrowserNext >>
aga khan iv
kutchan, hokkaido
richard greenblatt
p6m seamaster
hibiscus syriacus
byron nelson
torres
phosphodiester bonds
chess master
tina wesson
leviathan number
blue monkey
john wooden
gasp, quebec
bubb rubb
reapportionment
jus ad bellum
death: at death's door
christl haas
adore
helen reddy
bee line
denis villeneuve
the friends & enemies of modern music
united states senate minority whip
zentradi
philadelphia city hall
wolfdog
claude jutra
assimilation (sociology)
intelligent whale
harri porten
spey river
francisco de ulloa
strait of anin
brent scowcroft
crystal cruises
counter enlightenment
carl strandlund
slave state
anne o. krueger
batch production
list of francophone male singers
nyk line