Paper Info
Title
Orientation Contrast Detection in Space-Variant Images
Abstract
In order to appropriately act in a dynamic environment, any biological or artificial agent needs to be able to locate object boundaries and use them to segregate the objects from each other and from the background. Since contrasts in features such as luminance, color, texture, motion and stereo may signal object boundaries, locations of high feature contrast should summon an agent's attention. In this paper, we present an orientation contrast detection scheme, and show how it can be adapted to work on a cortical data format modeled after the retino-cortical remapping of the visual field in primates. Working on this cortical image is attractive because it yields a high resolution, wide field of view, and a significant data reduction, allowing real-time execution of image processing operations on standard PC hardware. We show how the disadvantages of the cortical image format, namely curvilinear coordinates and the hemispheric divide, can be dealt with by angle correction and filling-in of hemispheric borders.
Year
DOI
Venue
2000
10.1007/3-540-45482-9_56
Biologically Motivated Computer Vision
Keywords
Field
DocType
high feature contrast,space-variant images,high resolution,image processing operation,cortical data,object boundary,cortical image,hemispheric divide,hemispheric border,artificial agent,cortical image format,orientation contrast detection,image processing,image formation,data reduction,field of view,real time
Field of view,Computer vision,Computer science,Image processing,Multiresolution analysis,Image segmentation,Image file formats,Contrast (statistics),Artificial intelligence,Luminance,Visual field
Conference
Volume
ISSN
ISBN
1811
0302-9743
3-540-67560-4
Citations 
PageRank 
References 
0
0.34
7
Authors
4
Name
Order
Citations
PageRank
Gregory Baratoff113917.01
Ralph Schönfelder200.34
Ingo Ahrns3234.20
Heiko Neumann464493.84