Paper
6 June 1987 A Connectionist Architecture For Computing Textural Segmentation
Edmond Mesrobian, Josef Skrzypek
Author Affiliations +
Proceedings Volume 0758, Image Understanding and the Man-Machine Interface; (1987) https://doi.org/10.1117/12.940077
Event: OE LASE'87 and EO Imaging Symposium, 1987, Los Angeles, CA, United States
Abstract
This project examines some parallel architectures designed for image processing, and then addresses their applicability to the problem of image segmentation by texture analysis. Using this information, and research into the structure of the human visual system, an architecture for textural segmentation is proposed. The underlying premise is that textural segmentation can be achieved by recognizing local differences in texture elements (texels). This approach differs from most of the previous work where the differences in global, second-order statistics of the image points are used as the basis for segmentation. A realistic implementation of this approach requires a parallel computing architecture which consists of a hierarchy of functionally different nodes. First, simple features are extracted from the image. Second, these simple features are linked together to form more complex texels. Finally, local and more global differences in texels or their organization are enhanced and linked into boundaries.
© (1987) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Edmond Mesrobian and Josef Skrzypek "A Connectionist Architecture For Computing Textural Segmentation", Proc. SPIE 0758, Image Understanding and the Man-Machine Interface, (6 June 1987); https://doi.org/10.1117/12.940077
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KEYWORDS
Sensors

Image segmentation

Image processing

Computer architecture

Parallel computing

Image filtering

Computer programming

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