This paper describes a complete approach to detect, localize and describe network patterns. Such texture is automatically detected with Gaussian derivative kernels and Fisher linear discriminant analysis; line closure and thinning is provided by morphological masking and line luminance profile fitting provides width estimation. Detection results on dermatological images are reported and discussed.

Line Detection and Texture Characterization of Network Patterns / Grana, Costantino; Cucchiara, Rita; Pellacani, Giovanni; Seidenari, Stefania. - STAMPA. - 2:(2006), pp. 275-278. ( International Conference on Pattern Recognition Hong Kong Aug 20-24) [10.1109/ICPR.2006.764].

Line Detection and Texture Characterization of Network Patterns

GRANA, Costantino;CUCCHIARA, Rita;PELLACANI, Giovanni;SEIDENARI, Stefania
2006

Abstract

This paper describes a complete approach to detect, localize and describe network patterns. Such texture is automatically detected with Gaussian derivative kernels and Fisher linear discriminant analysis; line closure and thinning is provided by morphological masking and line luminance profile fitting provides width estimation. Detection results on dermatological images are reported and discussed.
2006
Inglese
International Conference on Pattern Recognition
Hong Kong
Aug 20-24
Proceedings of International Conference on Pattern Recognition
2
275
278
9780769525211
IEEE Computer Society
STATI UNITI D'AMERICA
Los Alamitos, CA
Internazionale
Contributo
line detection; texture; network patterns
Grana, Costantino; Cucchiara, Rita; Pellacani, Giovanni; Seidenari, Stefania
Atti di CONVEGNO::Relazione in Atti di Convegno
273
4
Line Detection and Texture Characterization of Network Patterns / Grana, Costantino; Cucchiara, Rita; Pellacani, Giovanni; Seidenari, Stefania. - STAMPA. - 2:(2006), pp. 275-278. ( International Conference on Pattern Recognition Hong Kong Aug 20-24) [10.1109/ICPR.2006.764].
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info:eu-repo/semantics/conferenceObject
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/464376
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