Texture recognition for frog identification
Yükleniyor...
Dosyalar
Tarih
2012-11-02
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ACM SIGMM
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper describes a visual processing technique for automatic frog (Xenopus Laevis sp.) localization and identification. The problem of frog identification is to process and classify an unknown frog image to determine the identity which is recorded previously on an image database. The frog skin pattern (i.e. texture) provides a unique feature for identification. Hence, the study investigates three different kind of features (i.e. Gabor filters, granulometry, threshold set compactness) to extract texture information. The classifier is built on nearest neighbor principle; it assigns the query feature to the database feature which has the minimum distance. Hence, the study investigates different distance measures and compares their performance. The detailed results show that the most successful feature and distance measure is granulometry and weighted L1 norm for the frog identification using skin texture features.
Açıklama
Anahtar Kelimeler
Frog identification, Image processing, Distance measure, Granulometries, Image database, Localization and identification, Minimum distance, Nearest neighbors, Skin textures, Texture information, Texture recognition, Unique features, Visual-processing, Xenopus laevis, Classification (of information), Ecology, Query processing, Textures
Kaynak
MAED '12: Proceedings of the 1st ACM International Workshop on Multimedia Analysis for Ecological Data
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Cannavo, F., Nunnari, G., Kale, İ. & Tek, F. B. (2012). Texture recognition for frog identification. Paper presented at the MAED '12: Proceedings of the 1st ACM International Workshop on Multimedia Analysis for Ecological Data, 25-30. doi:10.1145/2390832.2390839
