How Can CNNs Use Image Position for Segmentation?
Rito MuraseMasanori SuganumaTakayuki OkataniPublished in: CoRR (2020)
Keyphrases
- segmentation method
- segmentation algorithm
- image segmentation
- image analysis
- multiscale
- single image
- test images
- segmented images
- grey level
- image pixels
- image regions
- image data
- adaptive thresholding
- input image
- image content
- optimal segmentation
- joint segmentation
- watershed transformation
- brain mr images
- image segments
- image edges
- homogeneous regions
- image representation
- image retrieval
- image segmentation algorithm
- textured images
- gray level images
- gray value
- low depth of field
- perceptual grouping
- segmentation accuracy
- microscopic images
- segmented regions
- watershed algorithm
- segmentation errors
- image features
- pixel level
- position and orientation
- medical images
- energy functional
- shape prior
- region growing
- images of natural scenes
- microscopy images
- energy function
- level set
- graph cuts
- feature points
- super resolution
- scale space
- image processing
- markov random field
- color features
- background subtraction
- region segmentation
- intensity distribution
- colour images
- pixel values
- object segmentation
- multiple objects
- foreground and background
- image gradient
- intensity images
- pixel wise
- relative position