Wavelet-Based Energy Features for Glaucomatous Image Classification

• Published in: IEEE transactions on information technology in biomedicine Vol. 16; no. 1; pp. 80 - 87
• Main Authors: Dua, S., Acharya, U. R., Chowriappa, P., Sree, S. V.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2012
• Subjects: Adult; Aged; Algorithms; Bayes Theorem; Biomedical optical imaging; data mining; Diagnostic Techniques, Ophthalmological; Discrete wavelet transforms; Feature extraction; glaucoma; Glaucoma - diagnosis; Glaucoma - pathology; Humans; Image Interpretation, Computer-Assisted - methods; image texture; Matrix decomposition; Middle Aged; Reproducibility of Results; Retina; Support vector machines; Wavelet Analysis; wavelet transforms

Texture features within images are actively pursued for accurate and efficient glaucoma classification. Energy distribution over wavelet subbands is applied to find these important texture features. In this paper, we investigate the discriminatory potential of wavelet features obtained from the daub...