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https://hdl.handle.net/20.500.14279/2494
Τίτλος: | Image pattern algorithms using neural networks | Συγγραφείς: | Kasparis, Takis Eichmann, George Georgiopoulos, Michael N. |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Λέξεις-κλειδιά: | Image processing;Neural networks;Algorithms;Pattern recognition | Ημερομηνία Έκδοσης: | 1-Σεπ-1990 | Πηγή: | Hybrid Image and Signal Processing II; (1990), vol.1297, Technical Symposium on Optics, Electro-Optics, and Sensors, Orlando, FL, United States | Conference: | SPIE Conference Proceedings | Περίληψη: | 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. | URI: | https://hdl.handle.net/20.500.14279/2494 | ISSN: | 0277-786X | DOI: | 10.1117/12.21323 | Rights: | © 1990 SPIE | Type: | Conference Papers | Affiliation: | University of Central Florida The City College of New York |
Publication Type: | Peer Reviewed |
Εμφανίζεται στις συλλογές: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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