HTS: A new shape descriptor based on Hough Transform
| Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
|---|---|
| Data(s) |
27/05/2014
27/05/2014
09/09/2013
|
| Resumo |
In this paper we propose a novel method for shape analysis called HTS (Hough Transform Statistics), which uses statistics from Hough Transform space in order to characterize the shape of objects in digital images. Experimental results showed that the HTS descriptor is robust and presents better accuracy than some traditional shape description methods. Furthermore, HTS algorithm has linear complexity, which is an important requirement for content based image retrieval from large databases. © 2013 IEEE. |
| Formato |
974-977 |
| Identificador |
http://dx.doi.org/10.1109/ISCAS.2013.6572011 Proceedings - IEEE International Symposium on Circuits and Systems, p. 974-977. 0271-4310 http://hdl.handle.net/11449/76536 10.1109/ISCAS.2013.6572011 WOS:000332006801056 2-s2.0-84883413426 |
| Idioma(s) |
eng |
| Relação |
Proceedings - IEEE International Symposium on Circuits and Systems |
| Direitos |
closedAccess |
| Palavras-Chave | #Content based image retrieval #Digital image #Large database #Linear complexity #Shape analysis #Shape description #Shape descriptors #Transform statistics #Hough transforms |
| Tipo |
info:eu-repo/semantics/conferencePaper |
