JOURNAL ARTICLE

<title>Image pattern algorithms using neural networks</title>

Takis KasparisGeorge EichmannMichael GeorgiopoulosGregory L. Heileman

Year: 1990 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 1297 Pages: 298-306   Publisher: SPIE

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.

Keywords:
Computer science Artificial intelligence Artificial neural network Pattern recognition (psychology) Hough transform Segmentation Identification (biology) Image segmentation Image (mathematics) Image texture Process (computing) Texture (cosmology) Computer vision Contextual image classification Object (grammar) Cognitive neuroscience of visual object recognition

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Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Digital Imaging for Blood Diseases
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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