Image pattern algorithms using neural networks

Takis Kasparis; George Eichmann; Michael Georgiopoulos; Gregory L. Heileman

doi:10.1117/12.21323

1 September 1990 Image pattern algorithms using neural networks

Takis Kasparis, George Eichmann, Michael Georgiopoulos, Gregory L. Heileman

Proceedings Volume 1297, Hybrid Image and Signal Processing II; (1990) https://doi.org/10.1117/12.21323
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

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.

Citation Download Citation

Takis Kasparis, George Eichmann, Michael Georgiopoulos, and Gregory L. Heileman "Image pattern algorithms using neural networks", Proc. SPIE 1297, Hybrid Image and Signal Processing II, (1 September 1990); https://doi.org/10.1117/12.21323

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