Title
Image Pattern Algorithms Using Neural Networks
Abstract
The ability to classify texture regions in images is considered to be an important aspect of scene analysis. The information gained from such classification can be used by a computer vision system to assist in image segmentation as well as object identification. In this paper, the use of a neural network model in performing classification of images containing regular textures is investigated. The texture features used in the classification process are Hough transform-based descriptors. The performance and capabilities of the neural network approach are then compared to classical technique utilizing a linear associative memory.
Publication Date
12-1-1990
Publication Title
Proceedings of SPIE - The International Society for Optical Engineering
Volume
1297
Number of Pages
298-306
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0025632128 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0025632128
STARS Citation
Kasparis, T.; Eichmann, G.; and Georgiopoulos, M., "Image Pattern Algorithms Using Neural Networks" (1990). Scopus Export 1990s. 1450.
https://stars.library.ucf.edu/scopus1990/1450